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The Optimization of Transportation Costs in Logistics Enterprises with Time-Window Constraints

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  • Qingyou Yan
  • Qian Zhang

Abstract

This paper presents a model for solving a multiobjective vehicle routing problem with soft time-window constraints that specify the earliest and latest arrival times of customers. If a customer is serviced before the earliest specified arrival time, extra inventory costs are incurred. If the customer is serviced after the latest arrival time, penalty costs must be paid. Both the total transportation cost and the required fleet size are minimized in this model, which also accounts for the given capacity limitations of each vehicle. The total transportation cost consists of direct transportation costs, extra inventory costs, and penalty costs. This multiobjective optimization is solved by using a modified genetic algorithm approach. The output of the algorithm is a set of optimal solutions that represent the trade-off between total transportation cost and the fleet size required to service customers. The influential impact of these two factors is analyzed through the use of a case study.

Suggested Citation

  • Qingyou Yan & Qian Zhang, 2015. "The Optimization of Transportation Costs in Logistics Enterprises with Time-Window Constraints," Discrete Dynamics in Nature and Society, Hindawi, vol. 2015, pages 1-10, August.
    • Handle: RePEc:hin:jnddns:365367
    DOI: 10.1155/2015/365367
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    Cited by:

    1. Xinfeng Yan & Shakhrukh Madjidov & Habiba Halepoto & Muhammad Ikram, 2021. "Developing a Framework for the Optimization Processes of Logistics Costs: A Hurwitz Criterion Approach," SAGE Open, , vol. 11(4), pages 21582440211, October.
    2. Shyamali Ghosh & Karl-Heinz Küfer & Sankar Kumar Roy & Gerhard-Wilhelm Weber, 2023. "Type-2 zigzag uncertain multi-objective fixed-charge solid transportation problem: time window vs. preservation technology," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 31(1), pages 337-362, March.

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