Hybrid simulated annealing–slime mould algorithm for the non-permutation flow-shop scheduling problem DOI

Anran Zhao,

Peng Liu, Xiyu Gao

et al.

Engineering Optimization, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 13

Published: Oct. 8, 2024

The non-permutation flow-shop scheduling problem (NPFSP) is a more general type of than the permutation (PFSP). It features large solution space and highly complex. In this study, novel metaheuristic algorithm proposed for NPFSP, where makespan objective. specific implementation process as follows. First, mathematical model NPFSP constructed. Secondly, encoding decoding rules are designed to establish association between solutions PFSP NPFSP. Subsequently, hybrid simulated annealing–slime mould proposed. Finally, series control experiments conducted based on Demirkol benchmark. statistical results show effectiveness in solving

Language: Английский

A multi-objective differential evolution algorithm for the distributed hybrid flowshop scheduling problem with deteriorating jobs DOI
Xingping Sun, Yunlu Gong, Hongwei Kang

et al.

Engineering Optimization, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 33

Published: Jan. 10, 2025

For longevity in the market, manufacturers must strike a balance between monetary benefits and production capability. This article investigates distributed hybrid flowshop scheduling problem with deteriorating jobs, objective of minimizing makespan mean tardiness. A mathematical model for is constructed. To minimize goals, multi-objective discrete differential evolution (MODDE) method put forward. achieving optimization two-strategy initialization operation forth. local search strategy tailored to used improve algorithm's exploratory power. The proposed MODDE compared currently well-known techniques, demonstrating considerable performance gains. outcome shows that above methodology effective tackling problem.

Language: Английский

Citations

2
Scheduling distributed heterogeneous non-permutation flowshop to minimize the total weighted tardiness DOI
Fuli Xiong,

Siyuan Chen,

Ningxin Xiong

et al.

Expert Systems with Applications, Journal Year: 2025, Volume and Issue: unknown, P. 126713 - 126713

Published: Feb. 1, 2025

Language: Английский

Citations

1
A cooperative Q-learning-based memetic algorithm for distributed assembly heterogeneous flexible flowshop scheduling DOI
Jiawen Deng, Jihui Zhang, Shengxiang Yang

et al.

Expert Systems with Applications, Journal Year: 2025, Volume and Issue: unknown, P. 128198 - 128198

Published: May 1, 2025

Language: Английский

Citations

0
Hybrid simulated annealing–slime mould algorithm for the non-permutation flow-shop scheduling problem DOI

Anran Zhao,

Peng Liu, Xiyu Gao

et al.

Engineering Optimization, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 13

Published: Oct. 8, 2024

The non-permutation flow-shop scheduling problem (NPFSP) is a more general type of than the permutation (PFSP). It features large solution space and highly complex. In this study, novel metaheuristic algorithm proposed for NPFSP, where makespan objective. specific implementation process as follows. First, mathematical model NPFSP constructed. Secondly, encoding decoding rules are designed to establish association between solutions PFSP NPFSP. Subsequently, hybrid simulated annealing–slime mould proposed. Finally, series control experiments conducted based on Demirkol benchmark. statistical results show effectiveness in solving

Language: Английский

Citations

0