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Multi Objective Optimization of Coordinated Scheduling of Cranes and Vehicles at Container Terminals

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  • Seyed Mahdi Homayouni
  • Sai Hong Tang

Abstract

According to previous researches, automated guided vehicles and quay cranes in container terminals have a high potential synergy. In this paper, a mixed integer programming model is formulated to optimize the coordinated scheduling of cranes and vehicles in container terminals. Objectives of the model are to minimize total traveling time of the vehicles and delays in tasks of cranes. A genetic algorithm is developed to solve the problem in reasonable computational time. The most appropriate control parameters for the proposed genetic algorithm are investigated in a medium size numerical test case. It is shown that balanced crossover and mutation rates have the best performance in finding a near optimal solution for the problem. Then, ten small size test cases are solved to evaluate the performance of the proposed optimization methods. The results show the applicability of the genetic algorithm since it can find near optimal solutions, precisely and accurately.

Suggested Citation

  • Seyed Mahdi Homayouni & Sai Hong Tang, 2013. "Multi Objective Optimization of Coordinated Scheduling of Cranes and Vehicles at Container Terminals," Mathematical Problems in Engineering, Hindawi, vol. 2013, pages 1-9, June.
    • Handle: RePEc:hin:jnlmpe:746781
    DOI: 10.1155/2013/746781
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    Cited by:

    1. Damla Kizilay & Deniz Türsel Eliiyi, 2021. "A comprehensive review of quay crane scheduling, yard operations and integrations thereof in container terminals," Flexible Services and Manufacturing Journal, Springer, vol. 33(1), pages 1-42, March.
    2. Dalila B. M. M. Fontes & S. Mahdi Homayouni, 2023. "A bi-objective multi-population biased random key genetic algorithm for joint scheduling quay cranes and speed adjustable vehicles in container terminals," Flexible Services and Manufacturing Journal, Springer, vol. 35(1), pages 241-268, March.

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