Hybrid Variable Neighborhood Search Algorithm for the Multi-objective Distributed Permutation Flowshop Scheduling Problem with Sequence-Dependent Setup Times | IEEE Conference Publication | IEEE Xplore

Hybrid Variable Neighborhood Search Algorithm for the Multi-objective Distributed Permutation Flowshop Scheduling Problem with Sequence-Dependent Setup Times


Abstract:

This paper addresses the multi-objective distributed permutation flowshop scheduling problem with sequence-dependent setup times (MODPFSP_SDST), whose optimization object...Show More

Abstract:

This paper addresses the multi-objective distributed permutation flowshop scheduling problem with sequence-dependent setup times (MODPFSP_SDST), whose optimization objectives are the makespan, the total energy consumption and the noise emission. An effective hybrid variable neighborhood search (HVNS) algorithm is proposed for solving this problem. HVNS utilizes a probabilistic matrix to store structural information of the promising solution, and then employs matrix-based search operators to execute variable neighborhood search. Additionally, the objective-oriented local intensification search is integrated to further enhance solution quality. Simulations and comparisons demonstrate the effectiveness of HVNS in solving the MODPFSP_SDST.
Date of Conference: 06-10 October 2024
Date Added to IEEE Xplore: 20 January 2025
ISBN Information:
Conference Location: Kuching, Malaysia

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