EURO 2024 Copenhagen
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3626. A new Simuheuristic for Stochastic Cross-Dock Scheduling Problem With Time Windows Under Uncertainty

Invited abstract in session MB-58: Heuristics for Vehicle Routing 3, stream VeRoLog - Vehicle Routing and Logistics.

Monday, 10:30-12:00
Room: S07 (building: 101)

Authors (first author is the speaker)

1. Wei Yang
School of management, Northwestern Polytechnical University
2. Yang Wang
School of Management, Northwestern Polytechnical University
3. Jin-Kao Hao
LERIA, Université d’Angers

Abstract

Cross-docking, a rapid logistics strategy, emerges not just as an option but as a strategic necessity in the era of just-in-time inventory and manufacturing systems. In this context, we study a novel stochastic cross-dock scheduling problem considering uncertain truck arrival times to minimize the total penalty of untransferred goods and truck departure delay. A new hybrid genetic simheuristic framework is proposed that embeds a simulation-based local search into a variable neighborhood decent (VND) algorithm. VND optimizes on the deterministic version, in each iteration, if the current solution is identified as a promising solution (not necessarily a local optimal solution), SBLS, where the neighborhood is evaluated by the simulation instead of the deterministic objective value, is triggered in the expectation of finding a local optimal scheduling policy under the stochastic version. A fast evaluation technique for sample scenarios is designed, independent of the objective function, which allows the expectation of the objective under a given sample to be evaluated without simulation, thereby improving the efficiency of the search. And we extend the fast evaluation technique to scheduling problems with a similar structure. Finally, systematic experiments and analysis prove the efficiency of our proposed algorithmic framework and fast evaluation technique.

Keywords

Status: accepted

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