An integrated problem of handling equipment scheduling and storage space allocation for inbound containers at container terminals

Articles in Press

Document Type : Article

Authors

1 Msc student, Dept. of Industrial and Systems Engineering Isfahan University of Technology, Isfahan, Iran

2 isfahan university of technology

10.24200/j65.2025.65278.2413

Abstract

The increasing growth of container transportation has led container terminals, as the primary hubs of cargo transfer in the global supply chain, to continuously improve their efficiency and operations to be successful in this competitive industry. Various problems have arisen in the maritime logistics field owing to the division of container terminals into two sections, quayside and yardside. This study examines the integration of problems on the quayside and the yardside. Specifically, it simultaneously investigates the quay crane scheduling problem as a quayside problem, along with the yard truck scheduling problem, yard crane scheduling problem, and storage space allocation problem as part of the yardside problems. A new integer linear programming model has been presented for the integrated problem of equipment handling scheduling and storage location allocation. This problem aims to minimize the time required to complete containers and operational costs. These operational costs include unloading containers from vessels using a quay crane, moving them to the yard via yard trucks, and loading them using a yard crane. The integrated problem is classified under the category of NP-hard problems in terms of computational complexity. Furthermore, they were introduced and added to the model according to the problem structure to expedite the resolution of constraints under valid inequalities. To validate the model's accuracy, instances were designed, implemented in GAMS software, and executed using the CPLEX solver. The computational results demonstrate that the incorporation of valid inequalities across all instances reduces computational time. Furthermore, in instances involving larger problems, where the mathematical model was unable to determine the optimal solution within a reasonable time, the addition of valid inequalities yielded solutions with an average gap of 1.78% from the lower bound. By contrast, the proposed model without the inclusion of valid inequalities achieved solutions with a gap of 3.08% from the lower bound.

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Sharif Journal of Industrial Engineering & Management

Articles in Press, Accepted Manuscript
Available Online from 12 January 2025

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