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Particle swarm optimization based-algorithms to solve the two-machine cross-docking flow shop problem: just in time scheduling

Abstract

Cross-docking is an innovative logistical strategy which provides less inventory holding costs, less transportation costs and fast customer deliveries without storage in between or less than 24 hours. In this paper, we address the two-machine cross-docking scheduling problem within a Just-In-Time (JIT) context. This latter requires the punctuality and exactness of product deliveries. To satisfy this target, we aim to minimize the total earliness and tardiness, then early or tardy deliveries are discouraged. This study presents a great contribution in solving such NP-hard problem while applying different versions of the PSO (Particle Swarm Optimization) algorithm. One of them is hybridized with the Genetic Algorithm (GA). This latter is then shown to be the best one over computational experiments using different sized instances and by determining a percentage deviation from a developed lower bound.

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Correspondence to Imen Hamdi.

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Hamdi, I., Boujneh, I. Particle swarm optimization based-algorithms to solve the two-machine cross-docking flow shop problem: just in time scheduling. J Comb Optim 44, 947–969 (2022). https://doi.org/10.1007/s10878-022-00871-0

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Keywords

  • Cross-docking
  • Scheduling
  • PSO based-algorithms
  • Just in time
  • Lower Bound