دانشگاه صنعتی شریف
مهندسی صنایع و مدیریت
2676-4741
دوره 1-29
2
2014
02
20
PROJECT RISK ASSESSMENT BY A HYBRID APPROACH USING FUZZY-ANP AND FUZZY-TOPSIS
ارزیابی ریسک پروژه توسط رویکرد ترکیبی فرایند تحلیل شبکهیی و روش تاپسیس فازی
3
14
5241
FA
سید حسام الدین
ذگردی
بخش مهندسی صنایع، دانشگاه تربیت مدرس
احد
نظری
دانشکدهی معماری و شهرسازی، دانشگاه شهید بهشتی
ابراهیم
رضائی نیک
بخش مهندسی صنایع، دانشگاه تربیت مدرس
Journal Article
2011
01
09
Usually, projects are implemented in dynamic and complex environments due to their inherent uncertainties and risks. The purpose of risk management is to improve project performance via systematic risk assessment and response. <br>Companies have limited resources for managing all project risks; therefore, they need to prioritize the important ones. In particular, resources should be allocated to managing risks with higher priorities. In classical approaches, <br>probability and impact are two commonly used criteria in project risk assessment; however, these criteria do not sufficiently address all its aspects. Moreover, there may be interrelations and dependencies among the various criteria. <br> <br>In order to overcome these drawbacks, we proposed a practical framework for evaluating risk in projects. The proposed framework has three main steps. First, we identify project risks and determine those of importance to be evaluated by multiple attribute decision-making (MADM) techniques. Then, we use a fuzzy analytic network process (fuzzy-ANP) for calculating criteria weights. <br>The model is capable of considering dependencies among the different criteria. Also, the model calculates consistency indices for the fuzzy pair-wise comparison matrices. Finally, the outputs of fuzzy-ANP calculations are used in a fuzzy-based technique for order preference by similarity to ideal solution (fuzzy-TOPSIS) for ranking risks based on their importance. <br> <br>A case study of an Iranian power plant project is presented to demonstrate the applicability and performance of the proposed model. By different mechanisms, more than 100 risks were identified and categorized according to their sources. Next, we determine 10 important risks as alternatives for the fuzzy-ANP and fuzzy-TOPSIS procedures. We conclude that inadequate staff skill is the most important risk in such projects. Among other risks, difficulties in project financing are very important. <br> <br>In order to verify the obtained results and justify the proposed method, we calculated weights of the criteria (and sub-criteria) and ranked the risks using 6 different methods. We use the extent fuzzy-AHP and fuzzy <br>prioritization approach for calculating the weights of criteria (and sub-criteria). According to obtained results, significant differences are observed in the weights of sub-criteria when dependencies are considered. In <br>addition, there are no significant differences between rankings of risks for different methods. The results show that the proposed method is a suitable approach when performance ratings and weights are vague and imprecise.
در روشهای کلاسیک، ارزیابی ریسکهای پروژه براساس دو معیار احتمال وقوع و تأثیر آنها انجام میشود، ولی این معیارها بهتنهایی بیانگر تمام جنبههای ریسک نیستند. ضمن این که در دنیای واقعی بین معیارهای مختلف وابستگی وجود دارد. با هدف رفع کاستیهای یادشده، در این نوشتار یک ساختار سلسلهمراتبی برای ارزیابی ریسک پروژه پیشنهاد شده که وابستگی بین معیارها را در نظر میگیرد. در این ساختار ابتدا معیارها توسط فرایند تحلیل شبکهیی در محیط فازی ارزیابی، و وزن آنها تعیین میشود. در مرحلهی بعد، رتبهبندی ریسکها توسط الگوریتم تاپسیس در محیط فازی انجام میشود. بهمنظور اعتبارسنجی مدل، از طریق مطالعهی موردی در پروژههای نیروگاهی، بیش از ۱۰۰ ریسک شناسایی و ریسکهای مهم توسط <br>مدل پیشنهادی ارزیابی شده است. براساس نتایج کسبشده، علیرغم ابهام و غیر دقیق بودن دادههای مرتبط با ریسک پروژهها، مدل پیشنهادی برای مسائل دنیای واقعی مناسب و قابل کاربرد است.
https://sjie.journals.sharif.edu/article_5241_c5c2f1d55d01a4512a9c920c9a3db564.pdf
دانشگاه صنعتی شریف
مهندسی صنایع و مدیریت
2676-4741
دوره 1-29
2
2014
02
20
title{PRESENTING A MODEL BASED ON DATA MINING TO FORECAST CUSTOMER ATTRACTION \r\nUSING DECISION TREE IN CUSTOMER RELATIONSHIP MANAGEMENT
ارائهی مدلی مبتنی بر دادهکاوی برای پیشبینی جذب مشتری با استفاده از درخت تصمیم در «مدیریت ارتباط با مشتری»
15
23
5242
FA
ابوالفضل
کاظمی
دانشکدهی مهندسی صنایع و مکانیک، دانشگاه آزاد اسلامی واحد قزوین
محمد اسماعیل
بابائی
دانشکدهی مهندسی صنایع و مکانیک، دانشگاه آزاد اسلامی واحد قزوین
Journal Article
2011
01
19
With the rapid change in the business competitive environment, enterprise resource integration and innovative issues of business operation have gradually become the most important issues for businesses. Furthermore, many <br>organizations have implemented novel information technology and developed innovative application systems to enhance their competitive advantages. CRM systems can help organizations to gain potential new customers. Customer relationship management is a multi-perspective business paradigm which aims to maximize the benefits gained from relationships with customers. Today, in the quality-based and competitive world, which is known as knowledge time, customer attraction is very important. In line with the slogan, the customer is always <br>right, customer relation management is at the core of an organizational strategy. It plays an important role in four aspects: customer identification, customer attraction, customer retaining, and customer satisfaction. By analysis of customer life cycles, commercial organizations have obtained increases in customer value. Data store and data mining tools, and other customer relation management methods, have provided new opportunities for business. Data mining (DM) methodology has been of tremendous assistance to researchers in extracting <br>hidden knowledge and information inherited in their data. This paper, by the practical use of data mining in identification of potential customers, tries to help organizations to determine identification criteria of potential customers in the competitive environment of their business. It also presents mechanisms for identification of potential customers who have the ability to become real customers. In this paper, using a decision tree tool, we identify main criteria and determine their importance levels. We also consider that each main criterion consists of several sub-criteria, and we determine their importance in turning potential customers into real. We allow organizations to sell the process to each attendant in a direction which results in attendant (future customer) purchases, considering the criteria and sub-criteria identified.
در دنیای رقابتی و کیفیتگرای امروز، جذب مشتری از اهمیت زیادی برخوردار است. از این رو، «مدیریت روابط با مشتری» بهعنوان هستهی اصلی استراتژی سازمان در چهار بعد: شناسایی، جذب، نگهداری و رضایت مشتری به ایفای نقش میپردازد. سازمانها با تجزیه و تحلیل چرخهی زندگی مشتری به افزایش ارزش مشتری دست یافتهاند. این ادبیات با کاربرد عملی دادهکاوی در شناسایی مشتریان بالقوه، سعی دارد که معیارهای شناسایی این مشتریان را در محیط رقابتی کسب و کارشان تعیین، و سازوکاری برای بالفعلشدنِ آنان ارائه دهد. در این مطالعه، با استفاده از ابزار درخت تصمیم معیارهای اصلی و <br>زیرمعیارهایی را شناسایی و سپس میزان اهمیت آنها را تعیین میکنیم. از این طریق به سازمان این امکان داده میشود که در هر مراجعه فرایند فروش را به سمتی سوق دهد که منجر به خرید از سوی مراجعهکننده شود.
https://sjie.journals.sharif.edu/article_5242_9e6a5e4e4c3bb5cccc277d33f95850dc.pdf
دانشگاه صنعتی شریف
مهندسی صنایع و مدیریت
2676-4741
دوره 1-29
2
2014
02
20
A LAGRANGIAN RELAXATION METHOD FOR A MULTI-PRODUCT, MULTI-FACILITY PRODUCTION DISTRIBUTION MODEL IN A TWO-ECHELON SUPPLY CHAIN WITH PROBABILISTIC DEMANDS
ارائهی یک روش آزادسازی لاگرانژی برای یک مدل جدید تولید ـ توزیع در زنجیرهی تأمین دوسطحی چندمحصولی
25
39
5243
FA
روح الله
ذوالفقاری
دانشکدهی مهندسی صنایع، دانشگاه صنعتی امیر کبیر
فریبرز
جولای
دانشکدهی فنی، دانشگاه تهران
یاسر
موحدی
دانشکدهی مهندسی صنایع، دانشگاه صنعتی امیر کبیر
Journal Article
2011
01
23
In this paper, we consider a two-echelon supply chain problem with multi-facility, multi-period, multi-product and nondeterministic demands, in which, we assume that demands follow a normal distribution probability function <br>and that each product consists of several pre-determined parts. For solving the introduced model, we propose a hierarchical approach, based on the Lagrangian relaxation method. First, the problem is decomposed into two strategic and operational levels. <br> <br>At a strategic level, we respond to the following questions: Which facilities should be selected, how many demands are assigned to each selected facility, and which suppliers provide the necessary items for each facility. <br>The strategic level problem using the Lagrangian relaxation method leads to four subproblems. The dominance properties of these subproblems are examined, and optimal methods and a genetic algorithm are proposed to solve them. Then, these relaxed subproblems are transformed into a general strategic problem and the Lagrangian coefficients are updated. This procedure will be terminated when stop criteria are satisfied. These criteria are defined based on duality gap percentage, the number of iterations that have not been improved in the upper bound solution, and the total number of iterations. The output of strategic level decisions will be considered as input to operational level decisions. At the operational level, we want to know how many products must be produced during regular work time, how many products must be produced during overtime, and what the inventory level of each item is at the end of period times. The operational level problem is solved using commercial linear programming software. To evaluate the proposed solution algorithms, some random instances of the problem are generated and solved by the algorithms. We generate 18 classes of problem with different sizes, and consider a 120 months planning horizon for all problems. For each class of problem, 10 random instances are generated. All algorithms are run on a PC Pentium 4 with 2.8 GHz processor. <br> <br>The commercial software, Lingo 8.0, was able to solve only small size instances within reasonable computational time. The results of the proposed algorithms are compared with the solutions obtained by Lingo after 180 minutes. <br> <br>The results show the convergence of the proposed solution method based on Lagrangian relaxation to optimal solutions in the early iterations of the method. Also, the duality gaps do not show any trends to mean that the <br>efficiency of the method does not reduce by increasing the problem size.
در این نوشتار یک زنجیرهی تأمین دو سطحی ــٓشامل چندین مرکز توزیع، چند کارخانه با ظرفیت محدود و چند تأمین کنندهٓــ بهصورت یکپارچه مدلسازی شده است بهگونهیی که در آن چند محصول، شامل تعدادی قطعه، در جریان است. تقاضای مراکز توزیع از توزیع نرمال برخوردار است و مدل ارائهشده بهصورت سلسلهمراتبی، مسئله را به دو سطح استراتژیک و عملیاتی تقسیم میکند. در سطح اول، با استفاده از رویکرد لاگرانژ، مسئلهی آزادسازی و به چهار زیرمسئله تقسیم میشود. با بررسی شرایط بهینگی زیرمسئلهها، روشهای حل بهینه و الگوریتم ژنتیک برای آنها ارائه میشود. جوابهای حاصل از حل مسئلهی سطح اول بهعنوان ورودی سطح دوم در نظر گرفته میشود؛ مدل سطح دوم نیز که یک مدل برنامهریزی ریاضی خطی است توسط نرمافزارهای تجاری قابل حل است.
https://sjie.journals.sharif.edu/article_5243_e20c4bd42e51c70ddedb56ef62367172.pdf
دانشگاه صنعتی شریف
مهندسی صنایع و مدیریت
2676-4741
دوره 1-29
2
2014
02
20
OPTIMIZATION OF PERIODIC AND NON-PERIODIC INSPECTION INTERVALS FOR A MULTI- COMPONENT \r\n REPAIRABLE SYSTEM WITH FAILURE INTERACTION
بهینهسازی فواصل بازرسی (ثابت و غیرثابت) برای یک سیستم چند مؤلفهیی تعمیرپذیر با وابستگی خرابی
41
51
5244
FA
حمیدرضا
گلمکانی
دانشکدهی مهندسی صنایع، دانشگاه تفرش
حمید
موکدی
دانشکدهی مهندسی صنایع، دانشگاه تفرش
Journal Article
2011
03
08
This paper proposes an approach for finding periodic and non-periodic optimal inspection intervals for a multi-component repairable system with failure interaction. The failure of one component of the system is hard, i.e., as soon as it occurs, the system stops operating. Failures of other components are soft, namely; they do not cause the system to stop, but increase system operating costs and are detected only if inspection is performed. Thus, the components with soft failure are all inspected at scheduled inspection instances, and are minimally repaired if found to be failed. When the component with hard failure fails, it is also repaired. Each soft failure has no effect <br><br>on the behavior of the other components; however, any hard failure acts as a shock to other components, without inducing an instantaneous failure, but increasing their failure rate. The systems expected total cost includes inspection costs, repair costs, and penalty costs that are incurred due to time delay between real occurrence of soft failures and their detection at inspections. The objective is to determine both periodic and non-periodic optimal inspection intervals, which yield the minimum expected total cost of the system. <br><br> <br><br>In the proposed approach, the systems expected total cost is first formulated in terms of an inspection scheme. The occurrence of hard failures is modeled by a homogeneous Poisson process (HPP) with constant failure rate, and the occurrence of soft failures is modeled by a non-homogeneous Poisson process (NHPP) with increasing failure rate. Then, for obtaining the periodic optimal inspection scheme, the expected total cost is evaluated for all alternative periodic inspection schemes to identify the optimal one, which yields minimum cost. For obtaining the non-periodic optimal inspection scheme, a search algorithm, with a proposed heuristic cost function for calculating lower bounds, is employed to search through alternative inspection schemes to determine the optimal one. A numerical example is given to illustrate the proposed approach.
در این نوشتار مدلی برای بهینهسازی فواصل بازرسی (ثابت و غیرثابت) در یک سیستم چندمؤلفهیی با وابستگی خرابی بین مؤلفهها ارائه شده است. خرابیهای یکی از مؤلفههای سیستم از نوع سخت و خرابیهای سایر مؤلفهها از نوع نرم است. خرابی نرم موجب توقف سیستم نمیشود، ولی هزینههای عملیاتی سیستم را افزایش میدهد. خرابی سخت علاوه بر توقف <br><br>کامل سیستم، موجب افزایش نرخ خرابی سایر مؤلفههای سیستم نیز میشود. هدف این مطالعه تعیین بهترین فواصل زمانی (ثابت و غیرثابت) بین بازرسیهایمتوالی است، بهگونهیی که متوسط هزینهی کل کمینه شود. ابتدا هزینهی کل سیستم بهازای یک برنامهی بازرسی مشخص فرموله میشود و سپس، بهمنظور یافتن فواصل بهینهی بازرسی ثابت این هزینه برای برنامههای بازرسی مختلف با یکدیگر مقایسه میشود. بهمنظور یافتن فواصل بهینهی بازرسی غیر ثابت، الگوریتم جستوجوی $A^*$ بهکار گرفته شده است. برای تشریح بهتر مدل پیشنهادی، مثال عددی نیز آورده شده است.
https://sjie.journals.sharif.edu/article_5244_457cb8d53ab98345e9ac1d90f6dbee19.pdf
دانشگاه صنعتی شریف
مهندسی صنایع و مدیریت
2676-4741
دوره 1-29
2
2014
02
20
ANALYSIS OF EFFECTIVE FACTORS ON PRODUCTIVITY OF CHEMICAL COMPANIES
بررسی عوامل مؤثر بر بهرهوری در شرکتهای شیمیایی
53
62
5245
FA
مهدی
ابزری
دانشکده علوماداری و اقتصاد دانشگاه اصفهان
راحله
عالم
سازمان مدیریت صنعتی استان اصفهان
Journal Article
2011
03
08
Analysis of effective factors on productivity in the DMT Corporation in Isfahan is the purpose of this research. The improvement of productivity, based on two factors; internal and external, is studied. <br> <br>From an organizational point of view, external factors cannot be controlled, but, internal factors can be managed and improved. So, organizational structure, production management, production process, technical knowledge, <br>human resources (job satisfaction, proficiency, skill and motivation) and trait cognitive population, are effective factors on productivity. Like many companies, the DMT Co. has some problems and complexities in its industry, and some issues that have remained hidden from a management point of view. Company experts definitely have more information about mentioned problems, because they are aware of working processes. Thus, they can recognize effective factors more easily. <br> <br>In terms of purpose, this research is functional, and, in terms of research method, it is descriptive metrical. The statistical population of the research consists of all 75 experts in the company, which shows high precision. Data <br>collection has 2 steps: First is studying the literature of review, and second is the research survey, which requires some questionnaires. The data is collected using 47 questions, which are submitted to company experts in order <br>to measure their perceptions and attitudes. Respondents were assured complete anonymity, and no names or other means of identification were requested. Employees were asked to fill the questionnaire using a five point Likert scale (1; very low, 2; low, 3; moderate, 4; high and 5; very high). The questionnaire was used with reliability alpha 89% and high validity measured by the group of experts. <br> <br>Inferential statistics, such as X^2 , and Anova, have been used for analyzing the hypothesis. According to the results of statistical analysis and comparison with previous research, there is a positive relation between productivity and human resource factors, i.e; job satisfaction, motivation, technology, organizational structure, production process, production management, and technical knowledge. On the other hand, there is no positive relation between productivity and factors such as age, education, expert majors, work experience and proficiency of employee. <br> <br>Variance analysis based on age of respondent, shows that there is no difference between visions. But, according to the analysis of variance based on expert majors and work experience, there is a difference between visions.
هدف از این تحقیق بررسی عوامل مؤثر بر بهرهوری شرکت تولید مواد اولیهی الیاف مصنوعی (DMT) اصفهان است. برای این منظور ۷۵ نفر از کارشناسان شرکت انتخاب، و پرسشنامهیی با ۴۷ سؤال با طیف لیکرت تنظیم شد. سپس با نرمافزار SPSS و به <br>روشهای آمار توصیفی و آزمون خیدو تجزیه و تحلیل انجام شد. <br>نتایج نشان میدهد که با ارزیابی اکثریت کارشناسان، بهرهوری شرکت در سطح متوسط است. همچنین آنان عوامل انگیزش، تکنولوژی، ساختار سازمانی، فرایند تولید، مدیریت تولید و دانش فنی را در بهرهوری شرکت (DMT )مؤثر دانستند، اما عوامل جمعیتشناختی را در بهرهوری شرکت بیتأثیر قلمداد کردند. براساس نتایج به دست آمده، انگیزش مهمترین عامل مؤثر <br>بر بهرهوری شرکت(DMT) است و عوامل بعدی بهترتیب در بهرهوری شرکت مؤثر است. در این مطالعه اکثر کارشناسان شیوهی مدیریت شرکت را مؤثر دانستند و رضایتمندی والایی از کار در این شرکت داشتند.
https://sjie.journals.sharif.edu/article_5245_5753e5df55786955be65704988a34142.pdf
دانشگاه صنعتی شریف
مهندسی صنایع و مدیریت
2676-4741
دوره 1-29
2
2014
02
20
IMPROVEMENT OF ARTIFICIAL NEURAL NETWORK PERFORMANCE USING FUZZY LOGIC FOR EXCHANGE RATE FORECASTING
بهکارگیری منطق فازی برای بهبود عملکرد شبکههای عصبی مصنوعی بهمنظور پیشبینی نرخ ارز
63
71
5246
FA
مهدی
خاشعی
دانشکدهی مهندسی صنایع و سیستمها، دانشگاه صنعتی اصفهان
مهدی
بیجاری
دانشکدهی مهندسی صنایع و سیستمها، دانشگاه صنعتی اصفهان
فریماه
مخاطب رفیعی
دانشکدهی مهندسی صنایع و سیستمها، دانشگاه صنعتی اصفهان
Journal Article
2011
04
03
Time series forecasting is an active research area that has drawn considerable attention for applications in a variety of areas. With the time series approach to forecasting, historical observations of the same variable are analyzed to develop a model describing the underlying relationship. Then, the established model is used in order to extrapolate the time series into the future. Improving forecasting, especially accurate time series forecasting, is an important yet often difficult task facing decision makers in many areas. <br><br> <br><br>Computational intelligence approaches, such as artificial neural networks (ANNs) and fuzzy logic, have gradually established themselves as popular tools for forecasting complicated financial markets. Fuzzy is one of the most <br><br>important soft computing tools, which can provide a powerful framework in order to cope with vague or ambiguous problems, and can express linguistic values and human subjective judgments of natural language. <br><br> <br><br>Artificial neural networks are flexible computing frameworks and universal approximators that can be applied to a wide range of forecasting problems with a high degree of accuracy. The major advantage of neural networks is their flexible nonlinear modeling capability. With ANNs, there is no need to specify a particular model form. Rather, the model is adaptively formed based on the features presented in the data. This data-driven approach is suitable for many empirical data sets, where no theoretical guidance is available to suggest an appropriate data generating process. Despite the advantages cited for them, ANNs have weaknesses, one of the most important of which is their requirement of large amounts of data in order to yield accurate results. Both theoretical <br><br>and empirical findings have indicated that integration of different models can be an effective way of improving upon their predictive performance and also overcoming the limitations of single models, especially when the models in combination are quite different. <br><br> <br><br>In this paper, a new hybrid model of artificial neural networks is proposed based on the basic concepts of fuzzy logic, in order to overcome the data restriction of neural networks and yield more accurate results than traditional <br><br>ANNs in situations of short time spans. In the proposed model, instead of using crisp parameters in each layer, fuzzy parameters in the form of triangular fuzzy numbers are applied for related parameters of these layers. In this way, the proposed model can search the feasible spaces easily and more efficiently for finding the optimum values of parameters. The empirical results of exchange rate forecasting indicate that the hybrid model is more satisfactory than its components, i.e, artificial neural networks and fuzzy regression models.
روشهای هوش محاسباتی، همچون شبکههای عصبی مصنوعی و منطق فازی، بهعنوان ابزاری محبوب بهمنظور پیشبینی بازارهای پیچیدهی مالی معرفی شدهاند. دقت پیشبینیها ازجمله مهمترین مشخصههای مدلهای پیشبینی است و تلاش <br><br>برای بهبود بخشیدن کارایی مدلهای سریهای زمانی هرگز متوقف نشده است. امروزه علیرغم روشهای متعدد پیشبینی سریهای زمانی که در چند دههی اخیر پیشنهاد شدهاند، هنوز پیشبینی نرخهای ارز، کار بسیار دشواری محسوب میشود. در این مطالعه، مدل ترکیبی جدیدی از شبکههای عصبی مصنوعی براساس مفاهیم پایهیی منطق و مجموعههای فازی، بهمنظور <br><br>حصول نتایج دقیقتر در موقعیتهایی با دورههای کوتاهتری از زمان ارائه شده است. نتایج حاصله در پیشبینی نرخ ارز بیانگر کارآیی روش مذکور در پیشبینی نرخ ارز نسبت به مدلهای تشکیلدهندهی خود است.
https://sjie.journals.sharif.edu/article_5246_33f2f4d02ab7d8518ea6e6f5771a4eff.pdf
دانشگاه صنعتی شریف
مهندسی صنایع و مدیریت
2676-4741
دوره 1-29
2
2014
02
20
SIMULATION OF JIT MULTISTAGE SUPPLY CHAIN AND OPTIMIZATION OF OBJECTIVES
شبیهسازی زنجیرهی تأمین چندسطحی تحت سیستم بههنگام، و بهینهسازی اهداف آن
73
81
5247
FA
سیدکمال
چهارسوقی
گروه مهندسی صنایع، دانشگاه تربیت مدرس
آرمان
ساجدی نژاد
گروه مهندسی صنایع، دانشگاه تربیت مدرس
Journal Article
2011
04
11
It is difficult to determine an inventory level all through a supply chain (SC), in such a way that the desired objectives, such as effectiveness and responsiveness, can be obtained. Simulation is a means of solving problems <br><br>which cannot be solved by mathematical models, due to the complexity of the problems. <br><br> <br><br>Managers are, on the one hand, engaged in the strategic decision making of the chain, as well as various kinds of cooperation among members, and, on the other hand, with the quantities of inventory all through the chain. Strategies of each member of the supply chain and/or the whole supply chain can be based on meeting the needs (such as short-time delivery, producing new products, high level of availability of products, and so on) or effectiveness of the SC (low price of products, decreasing costs, and effectively using capital). <br><br> <br><br>Determining the level of inventory along a supply chain, in such a way that consumer satisfaction will be met to a favorable degree, taking into consideration responsiveness or effectiveness, is difficult. The present research is intended to study the inventory of a supply chain, as well as modeling the supply chain and determining multiple objectives in models for a four-stage, single-product supply chain. The use of metaheuristic techniques <br><br>leads to optimization of these variables, which helps decrease delay in both product delivery and inventory levels of SC. <br><br> <br><br>The present paper is aimed at JIT supply chain simulation together with optimization of the objectives of the SC. Variables of the simulation model include two types of Kanbans, namely; withdrawal and production, to determine the inventory level of SC and the batch size of delivery parts for each stage of the supply chain. Using metaheuristic techniques leads to optimization of these variables towards decreasing delay in the delivery and inventory levels of SC.
تعیین سطح موجودیها در طول زنجیرهی تأمین، بهمنظور نیل به اهداف متنوع زنجیره ــٓ نظیر رسیدن به سطح مطلوب پاسخگویی و کارایی ٓــ کاری دشوار به نظر میرسد. شبیهسازی ابزاری است برای حل مسائل پیچیدهیی که مدلهای ریاضی قادر به حل آنها نیستند. در این نوشتار زنجیرهی تأمین با الگوی تولید بههنگام و ترکیب شبیهسازی با بهینهیابی متغیرهای زنجیره مدل میشود. متغیرهای مدل شبیهسازی زنجیرهی تأمین عبارت است از: مقادیر دو نوع کانبان کششی و تولیدی برای تعیین سطح موجودی زنجیره، و میزان سایز دسته برای هر مرحله از زنجیرهی تأمین. با استفاده از تکنیک فراابتکاری، مقادیر این متغیرها چنان تعیین میشوند که اهدافی مانند کاهش دیرکرد در تحویل سفارشات و کاهش سطح موجودی در زنجیرهی تأمین، به سمت <br><br>بهینهشدن سوق داده میشوند.
https://sjie.journals.sharif.edu/article_5247_eb47f0ea0890ee209e4d10ed0475900c.pdf
دانشگاه صنعتی شریف
مهندسی صنایع و مدیریت
2676-4741
دوره 1-29
2
2014
02
20
A BRANCH-AND-BOUND ALGORITHM FOR A BI-OBJECTIVE OPERATING ROOM SCHEDULING PROBLEM
الگوریتم شاخه و کران برای یک مسئلهی دوهدفهی زمانبندی اطاقهای عمل
83
91
5248
FA
محمد
رنجبر
گروه مهندسی صنایع، دانشگاه فردوسی مشهد
عباس
غفوریان
دانشکدهی فنی مهندسی، دانشگاه علوم و فنون مازندران
Journal Article
2011
05
10
In this research, the operating room scheduling problem is studied. During recent years, this problem has attracted many researchers in an effort to reduce costs and raise the quality of health services. In this article, a <br><br>surgery is divided to four steps and the required resources for each step are determined, where surgeons and operating rooms are the main critical resources. <br><br>For this problem, a mixed integer programming model is developed, in which, assignment of patients to rooms and, also, the sequence of patient surgery, are determined, such that the bi-objective function, including additional work costs and idle time costs of surgeons, is minimized. This model is able to solve very small size problems in a reasonable time. Thus, a branch-and-bound algorithm has been developed to find an optimal solution, in each node of which, a patient is assigned to a room. The sequence of operations for patients <br><br>of a room and also for patients of a surgeon is established using parent-child relations of the search tree. Moreover, in order to prevent the enumeration of repetitive nodes or the extension of nodes that surely will not improve the best found solution, four properties are developed. This algorithm has been implemented in C++ programming language and a set of test problems are generated to evaluate its efficiency and analyze the sensitivity of some parameters. Based upon presented results, the solution time is increased if each of the three following parameters is increased: Number of patients, number of surgeons or average number of possible rooms for each patient. In addition, it seems that if 20% is added to the total surgery time of each surgeon, this <br><br>new time interval is proper to be considered as the working time interval, and longer intervals will not noticeably improve the quality of the optimal solution. It is shown in this paper that 0.25 is the best suitable coefficient <br><br>for the idle gaps of surgeons in the objective function.
موضوع مورد مطالعه در این نوشتار «زمانبندی اطاقهای عمل» است که در آن انجامِ هر عمل جراحی به چهار مرحله تقسیمبندی شده که منابع اصلی مورد نیاز هر مرحله جراحان و اطاقهای عمل هستند. این مسئلهتوسط یک مدل برنامهریزی عدد صحیح مختلط فرموله شده که در آن تخصیص بیماران به اطاقهای عمل و توالی عملهای بیماران هر اطاق طوری تعیین میشود که تابع هدف دومعیارهی میزان اضافهکاری جراحان و فواصل بیکاری بین جراحیهای آنها کمینه شود. بهمنظور حل مسئله، یک الگوریتم شاخه و کران توسعه داده شده و با تولید نمونه مسائلی، کارایی الگوریتم بررسی شده و حساسیت برخی پارامترها مورد تحلیل قرار گرفته است. <br><br>براساس نتایج ارائه شده، بهتر است ۲۰ درصد به طول کل زمان جراحیهای هر جراح اضافه کرده و آن را بهعنوان طول بازه کاری وی در نظر بگیریم زیرا بازههای کاری بزرگتر هیچگونه بهبود چشمگیری در جواب بهینه نخواهند داشت.
https://sjie.journals.sharif.edu/article_5248_5f133dbe63001965c8c77ad0b3bbf7f1.pdf
دانشگاه صنعتی شریف
مهندسی صنایع و مدیریت
2676-4741
دوره 1-29
2
2014
02
20
MODELING AND SENSITIVITY ANALYSIS OF VENDOR MANAGED INVENTORY SYSTEM BASED UPON \r\nSTACKELBERG GAME THEORY, ASSUMING THAT THE PRODUCER IS THE LEADER
مدلسازی و تحلیل حساسیت سیستم مدیریت موجودی توسط فروشنده براساس نظریهی بازی استاکلبرگ و با فرض رهبر بودن تولیدکننده
93
103
5249
FA
یحیی
زارع مهرجردی
دانشکدهی مهندسی صنایع، دانشگاه یزد
محمدصابر
فلاح نژاد
دانشکدهی مهندسی صنایع، دانشگاه یزد
حسن
رسایی
دانشکدهی مهندسی صنایع، دانشگاه یزد
Journal Article
2011
05
16
In this paper, we consider a supply chain consisting of one producer and multiple retailers, where the producer applies a vendor managed inventory in the supply chain. Production of a single product is assumed and the demand for this item in the retail market is a decreasing function, with respect to price. Although similar problems have been studied and analyzed by several researchers in the past, this work differs from others in several ways. <br> <br>The most important contributions of this article are: (1) Modeling centralized and decentralized states of the considered supply chain as non-linear programming. (2) Considering two situations for the decentralized supply chain: (a) producer sells the product at the same unit price to all retailers; (b) producer sells the product at different prices to retailers; (c) producing random data for parameters of the models and comparing centralized and decentralized state performances with each other; and (d) providing a sensitivity analysis for model parameters and vendor managed inventory systems. It is worthwhile to note that the decentralized state formulation is performed based on the Stackelberg game theory, and under the assumption that the <br>producer is the leader of the game. <br> <br>The results of our analysis indicate that; (i) differences in selling prices for retailers does not have much effect on the member profits of the supply chain, but can have a significant effect on prices; (2) sensitivity analysis of <br>the model parameters indicates that the influence of each parameter on system performance significantly depends on whether the overall demand of the system is less than the production rate or is equal to the production rate; (3) considering system performance in the centralized state as a benchmark, system <br>profit in a decentralized state is, on average, 0.94 centralized system profit. Also, for cases in which the overall demand of the system is less than the production rate, the difference between centralized and decentralized states is greater than that of the case whose production rate is equal to overall demand.
زنجیرهی تأمینی را در نظر بگیرید که شامل یک تولیدکننده و چندین خردهفروش است و تولیدکننده از رویکرد مدیریت موجودی توسط فروشنده برای کنترل موجودی در زنجیرهی تأمین استفاده میکند. در این زنجیره تولید یک محصول مورد نظر است و تقاضا برای این محصول در بازار خردهفروشها تابعی کاهشی از قیمت است. در این نوشتار طبق نظریهی بازی استاکلبرگ و با فرض رهبر بودن تولیدکننده، به مدلسازی و تحلیل این زنجیرهی تأمین خواهیم پرداخت. مشخصاً مدل زنجیرهی تأمین را در حالت متمرکز و غیر متمرکز ارائه خواهیم داد. پس از مقایسهی ساختارهای متمرکز و غیر متمرکز زنجیرهی تأمین با تولید مقادیر تصادفی برای پارامترهای مدلها، به تحلیلهای عمیقِ سیستم مدیریت موجودی توسط فروشنده خواهیم پرداخت.
https://sjie.journals.sharif.edu/article_5249_ba63fbb55bf253d5628300d469a04e1e.pdf
دانشگاه صنعتی شریف
مهندسی صنایع و مدیریت
2676-4741
دوره 1-29
2
2014
02
20
DETERMINING THE NUMBER OF MACHINES AND BUFFER CAPACITY IN FAILURE-PRONE PRODUCTION LINES TO OPTIMIZE PRODUCTION RATE
تعیین تعداد ماشین و حجم بافرها در خطوط تولید نامطمئن بهمنظور بهینهسازی نرخ تولید
105
115
5250
FA
مقصود
امیری
دانشکدهی مدیریت و حسابداری، دانشگاه علامه طباطبایی
علی
محتشمی
گروه مدیریت صنعتی، دانشگاه آزاد اسلامی واحد قزوین
Journal Article
2011
06
12
A production line consists of machines connected in series and separated by <br><br><br>buffer capacity. Each part is required to be processed on each machine during a <br><br><br>time called the service or process time. Material flow may be disrupted by <br><br><br>machine failure or by differences between the service times of the stations. <br><br><br>The inclusion of buffers increases the average production rate of the line by <br><br><br>limiting the propagation of distributions, but at an additional cost of capital <br><br><br>investment, floor space of the line and inventory. On the other hand, the <br><br><br>inclusion of parallel machines in a station increases its reliability and <br><br><br>results in higher production rate. Determining buffer size and number of <br><br><br>parallel machines in a station is a challenging problem. This paper formulates <br><br><br>the problem of determining the optimal (or near optimal) number of machines and <br><br><br>buffer capacities in failure-prone production and assembly lines to optimize <br><br><br>production rate. This paper also provides a methodology to solve this problem. <br><br><br>The objective is to maximize production rate with minimum machine purchase cost <br><br><br>and minimum total buffer size (A multi-objective formulation). The majority of <br><br><br>solution methods assume that the process times, time between failures and <br><br><br>repair times, are deterministic or exponentially distributed. This paper <br><br><br>relaxes these restrictions by proposing a simulation based methodology that can <br><br><br>consider general distribution functions for all parameters of production lines. <br><br><br>Considering the large number of factors in such problems (machines and buffers <br><br><br>of each station), we first use a two level fractional factorial design to <br><br><br>determine the more significant factors, and second, use a response surface <br><br><br>design to build a response surface metamodel as a production rate estimator, <br><br><br>based on different configurations of buffer capacity and number of machines. We <br><br><br>use the Lp-metric method as one of the powerful methods for multi-objective <br><br><br>problem solving that generates different solutions based on objective weights. <br><br><br>Finally, we use a genetic algorithm combined with the lines search method to <br><br><br>solve the multi objective model and to determine the optimal (or near optimal) <br><br><br>number of machines and buffer capacities in each station.
در این نوشتار بهمنظور افزایش نرخ تولید در خطوط تولید نامطمئن (امکان خرابی ماشینآلات وجود دارد)، مدلسازی مسئلهی تعیین تعداد ماشینها و بافرهای بین ماشینها بررسی، و یک متدولوژی برای حل مسئله ارائه میشود. هدف از این مطالعه بیشینهسازی نرخ تولید با کمترین هزینهی افزایش ماشینآلات و کمترین مقدار بافرهای میان ایستگاههاست. متدولوژی <br><br><br>پیشنهادی این مطالعه برخلاف تحقیقات پیشین با رویکردی واقعبینانهتر به خطوط تولید، فرض میکند که زمان پردازش ماشینآلات، نرخ خرابی و تعمیر ماشینآلات بهصورت زمانهای تصادفی بوده و میتوانند از هر تابع توزیعی تبعیت کنند. بهمنظور بهینهسازی (نزدیک بهینه) تعداد ماشینآلات و بافرها از تکنیکهای شبیهسازی، طراحی آزمایشها، متدولوژی سطح پاسخ، الگوریتم ژنتیک و جستوجوی خطی بهره میبرد.
https://sjie.journals.sharif.edu/article_5250_920f3691bb163444d28667b45fe634ad.pdf
دانشگاه صنعتی شریف
مهندسی صنایع و مدیریت
2676-4741
دوره 1-29
2
2014
02
20
MULTI-LAYER SINGLE ALLOCATION HUB SET COVERING PROBLEM
مکانیابی محور پوششی کامل چندلایه با تخصیص یگانه
117
125
5251
FA
حسین
کریمی
گروه مهندسی صنایع، دانشگاه شاهد
مهدی
بشیری
گروه مهندسی صنایع، دانشگاه شاهد
Journal Article
2011
07
09
Finding the location of hub facilities and the allocation of non-hub nodes to these located hub facilities are the aim of hub location problems. Commodities flow in the hub and spoke network in three phases; 1) Collecting: they move along their origin nodes to the assigned hub nodes. 2) Transferring: commodities flow through the hub arcs if necessary. 3) Distributing: commodities depart the hub network and arrive at destination nodes. Typical applications of hub locations include: airline passenger travel, telecommunication systems and postal networks. The hub location problem was originally introduced by OKelly (1986). Campbell (1994) provided the hub set and hub maximal covering problem with single and multiple allocations. In this work, we propose a multi-layer single allocation hub set covering problem over fully interconnected hub networks, and provide a formulation to this end. The postal service can be a multi-layer hub covering application. Postal companies <br>offer different delivery time pledges, such as next day delivery, to their customers. However, due to geographical distribution of cities and the structure of highways, delivery within 24 hours between all city pairs is <br>impossible if only ground transportation is employed. Chiefly, due to competitiveness, it is better for postal companies to check the feasibility of including airlines in their distribution networks. This issue motivates us to <br>introduce a multi layer model for hub covering problems, which can determine whether a ground or air route for each link is better in the hub network, in which the delivery time bound is guaranteed, as the covering radius. Trade hubs are another real application of the proposed approach. The trade growth of each country can occur if trade hubs are designed and developed properly. On the other hand, trade hubs connect most trade routes with some facilities to decrease total transportation costs with lowest delivery times, so, according to their geographic position, they should employ different modes of transportation system. We provide a clear example to introduce the model. For better illustration of the proposed model, a numerical example with four nodes <br>is provided and solved by the CPLEX solver. Moreover, we test the performance of the model on the AP data set. Results of the AP data set for problems of size n = 10, 20, 25, 40 and 50, are given. Since the AP data set does not consider multi-layer data, we consider two layers for these benchmarks as assumptions. The computed gap from the lower bound, using the CPLEX solver, shows the efficiency of the proposed approach. The results show that the problem lower bounds increase in a tighter covering radius, and the number of hub locations decreases in a looser covering radius.
مسئلهی مکانیابی محور عبارت است از انتقال کالا از مبدأها به مقصدها، که در آن بهجای ارتباط مستقیم میان هر دو نقطهی مبدأ و مقصد، کالاها از طریق محورها منتقل میشوند. در مکانیابی محور پوششیِ مورد بحث در این پژوهش، محدودیت ظرفیت برای مکانهای محور در نظر گرفته شده است. علاوه بر این، مفهوم لایه برای مسیرها تعریف، و مدلی چندلایهیی برای مسئلهی <br>مورد نظر فراهم شده است. استفاده از لایههای مختلف بهدلیل سودآوریشان اقتصادی است و در شبکهی محورهای تجاری و توزیع کالاهای پستی، این مدل را میتوان پیادهسازی کرد. همچنین با استفاده از روشی برمبنای الگوریتم شبیهسازی تبرید، رویهی جستوجویی برای مدل ارائه شده است که نتایج آن در مقایسه با نرمافزار بهینهسازی برنامهریزی خطی مورد تحلیل و بررسی قرار گرفته است. نتایج به دست آمده نشان میدهد که روش حل پیشنهادی در مقایسه با ابزار حل در نرمافزار بهینهسازی به جواب بهینهیی منجر میشود.
https://sjie.journals.sharif.edu/article_5251_51a613b546c97565d3d7512d05a74688.pdf
دانشگاه صنعتی شریف
مهندسی صنایع و مدیریت
2676-4741
دوره 1-29
2
2014
02
20
EVALUATION OF AUTHORIZED DEALERS IN AUTOMOTIVE AFTER SALES SERVICES COMPANIES BASED ON CUSTOMER VALUE USING PROMETHEE
ارزیابی نمایندگیهای خدمات پس از فروش خودرو مبتنی بر ارزش مشتری و با روش PROMETHEE
127
134
5252
FA
اکبر
اصفهانی پور
دانشکدهی مهندسی صنایع و سیستمهای مدیریت، دانشگاه صنعتی امیرکبیر
نجمه
بسطامی
دانشکدهی مهندسی صنایع، دانشگاه پیام نور تهران
Journal Article
2011
02
26
Today, there is a huge opportunity for after sales services companies to get more value by selling spare parts. To reach this ultimate goal, as well as to have more market share, the key issue is to distinguish between valuable and non-valuable authorized dealers as direct customers and main distribution channels of spare parts. Therefore, appropriate evaluation of these dealers is an important task for these companies. Here, we take an outranking approach for this evaluation. In order to rank a finite number of dealers, several criteria have to be defined. Hence, we are dealing with a multi criteria decision-making problem. The purpose of this paper is to develop a decision-making model for authorized dealer evaluation. In this regard, we determine suitable criteria based on the main concepts of customer value, namely; customer current value, customer potential value and customer loyalty. We run a survey to finalize the evaluation criteria, as well as to determine the weights of the criteria. Our <br>respondents were relevant experts who worked in an after sales services company. We applied the PROMETHEE method as a multi criteria decision making model for ranking of the authorized dealers at Saipa Yadak, as a real case. The ranking results showed that the proposed ranking model of this study can be considered as an appropriate guideline to deal with authorized company dealers, in terms of discounts, prices and other terms of contracts between them.
امروزه شناسایی نمایندگیهای پرارزش، بهعنوان اصلیترین کانال توزیع قطعات یدکی، برای سازمانهای خدمات پس از فروش در راستای تحقق استراتژی افزایش سهم بازار قطعات یدکی امری بسیار ضروری است. هدف از این مطالعه توسعهی یک مدل تصمیمگیری بهمنظور ارزیابی و رتبهبندی نمایندگیهای خدمات پس از فروش خودروست. به این منظور معیارهای اصلی برای ارزیابی سودآوری نمایندگیها با توجه به مفاهیم ارزش مشتری ــٓ شامل ارزش فعلی، ارزش بالقوه و وفاداریٓــ و با استفاده از نظر خبرگان تعیین شدهاند. سپس با استفاده از روش تصمیمگیری مدلی برای ارزیابی و رتبهبندی نمایندگیها ارائه شده است. <br>برای نشاندادن کاراییِ مدل پیشنهادی، دستهیی از نمایندگیهای شرکت سایپایدک با استفاده از این مدل ارزیابی و رتبهبندی شده است.
https://sjie.journals.sharif.edu/article_5252_e1f08ba5e897f8d1a11f8d0ab1f97f73.pdf
دانشگاه صنعتی شریف
مهندسی صنایع و مدیریت
2676-4741
دوره 1-29
2
2014
02
20
A METHOD FOR DISCONTINUOUS PRODUCTION PLANNING SYSTEMS WITH MULTIPLE OBJECTIVES AND MULTIPLE STAKEHOLDERS
روشی برای برنامهریزی تولید سیستمهای گسستهی چندمنظورهی چند ذینفعه
135
144
5253
FA
سید محمدعلی
خاتمی فیروز آبادی
دانشکده مدیریت و حسابدار، دانشگاه علامه طباطبایی (ره)
Journal Article
2011
08
03
In any organization, there are many stakeholders, whose points of view should be taken into account when planning. The involvement of different stakeholders in the decision making process is an important feature to be considered, not only for interpretation and making decisions based on their judgment, but also for their participation in research and the decision making process. A decision is evaluated as a suitable decision when all stakeholders are satisfied with the final decision, which means that the stakeholders should reach a consensus <br>on the decision. Stakeholder participation in the decision making process enhances respect for their opinions, as well as improving the learning process in the organization and better understanding of the studied system. Involvement of different stakeholders can improve the perception of a problem because of their diverse information, which may be ignored in the presence of just one stakeholder. Therefore, in any planning, it is necessary to consider all stakeholder objectives to reach a compromise. Stakeholder objectives may be in <br>conflict with each other, and a production plan based on just one stakeholder, however important he/she may be, may create problems in the organization. To overcome these problems, this paper intends to provide a set of linear programming models for each individual stakeholder, with their objectives, in order to discover whether or not stakeholder viewpoints are identical. If the solutions of the models are the same, then, we can claim there are no major conflicts between the stakeholders. Otherwise, it is necessary to aggregate the individual models to obtain a unique model and, therefore, a single solution. <br>To do this, a multi-objective programming model is established, which is an aggregation of individual linear programming models, in order to consider different stakeholder objectives. Solution of the aggregated model, using the LP metric method, can provide the final solution for an organization that satisfies stakeholder viewpoints as much as possible. The aim of the paper is to provide a methodology to consider different stakeholder viewpoints, with their objectives, in discontinuous production planning systems. Aggregation of individual stakeholder models to obtain a unique solution has been studied via multi-objective programming. The methodology has been applied to an electrical manufacturing company to show the abilities of the methodology. The results of the study show that company stakeholders are relatively satisfied with the solutions. However, there is some small dissatisfaction, which may always exist
هدف این نوشتار ارائه یک متدولوژی مناسب برای در نظر گرفتن دیدگاههای مختلفِ ذینفعان با اهداف متعارض آنها در برنامهریزی تولید است. وجود برنامه تولیدی که فقط به ایدههای یک ذینفع ــٓ هرچند مهمٓ ــ بپردازد عملاً سازمان را در پیادهسازی نتایج با مشکل مواجه میسازد. در تحقیق حاضر ضمن ایجاد مدلهای برنامهریزی خطی، جوابهای به دست آمده از نگاه هر ذینفع مورد بررسی قرار میگیرد. درصورت یکساننبودن جوابها، مدلهای هر ذینفع با استفاده از برنامهریزی چندمنظوره در هم ادغام <br>میشود. حل مدل برنامهریزی چندمنظوره با استفاده از روش معیار جامع، سازمان را موفق به دستیابی به برنامهریزی تولید میکند. چگونگی ادغام جوابهای مختلف به دست آمده از هر ذینفع در این نوشتار مورد مطالعه قرار گرفته است. قابلیتهای متدولوژی پیشنهادی در این مطالعه، با بهکارگیری در یک شرکت تولیدکننده لوازم برقی سنجیده شده است.
https://sjie.journals.sharif.edu/article_5253_0814e99dc08672d24af4c8bedafb21af.pdf
دانشگاه صنعتی شریف
مهندسی صنایع و مدیریت
2676-4741
دوره 1-29
2
2014
02
20
SIMULTANEOUSLY ESTIMATION OF REGRESSION COEFFICIENTS FOR CORRELATED MULTIPLE \r\nRESPONSES WITH CATEGORICAL DATA
تخمین همزمان سطوح چندپاسخی وابسته بههم برای دادههای طبقهبندی شده
145
157
5254
FA
رضا
کامران راد
گروه مهندسی صنایع، دانشگاه شاهد
مهدی
بشیری
گروه مهندسی صنایع، دانشگاه شاهد
Journal Article
2011
08
28
Regression coefficient estimation of multiple responses is an important problem which has been previously studied. In this paper, a heuristic algorithm has been proposed to estimate regression coefficients of the relationship between control and correlated binary response variables. In this paper, a log-linear model has been used for analyzing experiments with more than one categorical response variable. The considered model in this study is called the saturated log-linear model, because the responses (2 responses) of this research are <br>cross correlated. To estimate the parameters of the logistic regression model for dependent responses, a heuristic iterative nonlinear method is used to maximize the number of concordance. <br> <br>The proposed heuristic approach is a development of the parameter estimation method (Yeh et al. 2009) that is presented for the univariate binary logistic regression model, which is then applied to estimate the parameters of the log-linear model. <br> <br>The proposed approach uses the concept of concordance. Concordance means that the joint probability of the occurrence of dependent responses in each treatment is more than other probabilities in the same treatment. Although much research has been undertaken on issues of single and multiple continuous responses and single categorical response problems, this study presents a new approach for simultaneous estimation of the parameters of the log-linear model with correlated categorical responses. Hence, it can be useful in real experimental cases. To indicate the efficiency of the heuristic method, the proposed approach has been compared to existing approaches in some hypothetical examples with simulated data and different sizes (seven, ten and fifteen <br>treatments). Thus, initially, the parameter values of dependent responses were estimated, and then, the model parameters for each response variable were calculated separately. After estimating parameters, the joint probability values were obtained for both cases of dependent and independent response problems. <br> <br>It should be noted that joint probability values, in the case of independence between variables, are equal to the product of the individual probabilities of two independent responses. <br> <br>Because the number of concordance in the proposed heuristic method is greater than in the second case (independence between variables), the proposed heuristic method represents a good performance compared to the estimated coefficients of individual variables, on the basis of concordance measurement. Also, the proposed approach has been analyzed for a real case study from the literature, and with the existing method of (Yeh et al. 2009), and analyses show the efficiency of the proposed approach.
هدف این نوشتار، تخمین رابطهی بین متغیرهای کنترلی و متغیرهای پاسخ از نوع دادههای طبقهبندی شده و دارای وابستگی با استفاده از یک روش ابتکاری است. در این نوشتار با استفاده از مدل لگاریتم خطی، آزمایشهایی با بیش از یک متغیر پاسخ طبقهبندی شده تحلیل و مدلسازی شده است. برای تخمین پارامترهای مدل رگرسیون لجستیک برای پاسخهای وابسته (دو متغیر پاسخ وابسته)، از یک روش ابتکاری غیرخطی تکرارپذیر با هدف بیشینهکردن تعداد انطباقها استفاده شده است. مقایسهی نتایج حاصل از روش ابتکاری با نتایج به دست آمده در حالت استقلال متغیرها و یکی از روشهای موجود ــٓبرای مثالهای فرضی با دادههای شبیهسازی شده و یک مطالعهی موردی با اندازههای متفاوتٓــ نشان میدهد که روش ابتکاری پیشنهادی در مقایسه با یکی از روشهای موجود و روش تخمین جداگانه ضرایب متغیرهای پاسخ براساس شاخص میزان انطباق و شاخص حداکثر درستنمایی از عملکرد مناسب برخوردار است.
https://sjie.journals.sharif.edu/article_5254_b479a8451028d320b0268de835a7352a.pdf