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

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.