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

Anran Zhao,

Peng Liu, Xiyu Gao

и другие.

Engineering Optimization, Год журнала: 2024, Номер unknown, С. 1 - 13

Опубликована: Окт. 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

Язык: Английский

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

и другие.

Engineering Optimization, Год журнала: 2025, Номер unknown, С. 1 - 33

Опубликована: Янв. 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.

Язык: Английский

Процитировано

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

Siyuan Chen,

Ningxin Xiong

и другие.

Expert Systems with Applications, Год журнала: 2025, Номер unknown, С. 126713 - 126713

Опубликована: Фев. 1, 2025

Язык: Английский

Процитировано

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

и другие.

Expert Systems with Applications, Год журнала: 2025, Номер unknown, С. 128198 - 128198

Опубликована: Май 1, 2025

Язык: Английский

Процитировано

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

Anran Zhao,

Peng Liu, Xiyu Gao

и другие.

Engineering Optimization, Год журнала: 2024, Номер unknown, С. 1 - 13

Опубликована: Окт. 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

Язык: Английский

Процитировано

0