عنوان مقاله [English]
In this paper, we endeavor to develop a hybrid problem of location, pricing and queuing in a network with M customer nodes and N potential server nodes. In fact, we propose a bi-objective model for the facility location problem subject
to congestion and a pricing policy. The model is formulated by means of a queuing framework, in which each facility behaves as an M/M/m/k queuing system, where m is the number of servers in each facility and k is the queuing system capacity. We consider two simultaneous perspectives for this problem; (1) customers (desire to limit times of waiting for service) and (2) service provider (desire to increase profit). Our mathematical model contains two
simultaneous objectives, including (I) maximizing profit and (II) minimizing the amount of waiting time in the whole network. In our model, we assume that different prices are provided at different facilities for services.
Furthermore, capacity constraints are considered to bring the problem even closer to reality. This assumption is referred to as mill pricing, and gas stations and parking places are examples of mill pricing. The proposed model
belongs to a class of mixed-integer nonlinear programming models and the class of NP-hard problems. Therefore, we presented a multi-objective vibration damping optimization (MOVDO) algorithm to solve the mathematical model.
Finally, the performance of the proposed algorithm is compared with the literature and different test problems are generated and analyzed.