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Deadlock control and hybrid social spider scheduling algorithm for two-stage assembly permutation flowshop with limited buffers.

Authors :
Cao, Feng
Feng, Yanxiang
Wang, Siyi
Zhang, Guanghui
Xing, Keyi
Source :
Expert Systems with Applications. Jul2024, Vol. 245, pN.PAG-N.PAG. 1p.
Publication Year :
2024

Abstract

This paper focuses on the deadlock control and scheduling problem of two-stage assembly permutation flowshop with limited buffers. In such a system, all parts are first processed in a permutation flowshop, then assembled into final products. The objective is to find a feasible schedule, including a manufacturing subschedule and an assembly subschedule, to minimize makespan. Owing to limited buffers, not only may the blocking phenomenon appear in the system operation, but also some manufacturing subschedules may lead to deadlock states, making them unavailable. To obtain a feasible schedule, this work first proposes a deadlock control or an availability detection and amendment (ADA) algorithm to determine whether a manufacturing subschedule is available, and convert unavailable ones to available ones. Then by embedding ADA into a social spider algorithm (SSA), a hybrid social spider algorithm (HSSA) is developed for computing feasible schedules. In HSSA, an improved heuristic search algorithm is proposed to generate a better initial population, and a simplified variable neighborhood search algorithm is designed and incorporated into HSSA to enhance its searching ability. Finally, HSSA is tested on instances, showing its superiority over SSA in performance. The effect of buffer size on the scheduling objective is discussed. • The availability of manufacturing subschedules is determined. • The unavailable subschedules can be transformed into available ones. • A hybrid social spider algorithm is developed for computing feasible schedules. • Using an improved heuristic search algorithm to obtain a better initial population. • The local search ability is enhanced by a simplified variable neighborhood search. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
09574174
Volume :
245
Database :
Academic Search Index
Journal :
Expert Systems with Applications
Publication Type :
Academic Journal
Accession number :
176151920
Full Text :
https://doi.org/10.1016/j.eswa.2023.122744