Optimizing distributed reentrant heterogeneous hybrid flowshop batch scheduling problem: Iterative construction-local search-reconstruction algorithm DOI
Peng He, Biao Zhang, Chao Lu

et al.

Swarm and Evolutionary Computation, Journal Year: 2024, Volume and Issue: 90, P. 101681 - 101681

Published: Aug. 18, 2024

Language: Английский

Novel MILP and CP models for distributed hybrid flowshop scheduling problem with sequence-dependent setup times DOI
Leilei Meng, Kaizhou Gao, Yaping Ren

et al.

Swarm and Evolutionary Computation, Journal Year: 2022, Volume and Issue: 71, P. 101058 - 101058

Published: March 25, 2022

Language: Английский

Citations

92
Modelling and optimization of distributed heterogeneous hybrid flow shop lot-streaming scheduling problem DOI
Weishi Shao, Zhongshi Shao, Dechang Pi

et al.

Expert Systems with Applications, Journal Year: 2022, Volume and Issue: 214, P. 119151 - 119151

Published: Nov. 1, 2022

Language: Английский

Citations

60
LS-HH: A Learning-Based Selection Hyper-Heuristic for Distributed Heterogeneous Hybrid Blocking Flow-Shop Scheduling DOI
Zhongshi Shao, Weishi Shao, Dechang Pi

et al.

IEEE Transactions on Emerging Topics in Computational Intelligence, Journal Year: 2022, Volume and Issue: 7(1), P. 111 - 127

Published: May 25, 2022

As the development of economic globalization, distributed manufacturing has become common in modern industries. The scheduling production resources multiple centers becomes an emerging topic. This paper is first attempt to address a heterogeneous hybrid blocking flow-shop problem (DHHFSP-B) with minimization makespan. Compared traditional single scheduling, DHHFSP-B considers collaborative flow lines layout and processing performance as well no intermediate buffers. We firstly present mixed-integer linear programming model formulate then propose learning-based selection hyper-heuristic framework (LS-HH) for solving it. LS-HH contains high-level strategy low-level heuristics. In strategy, learning probability built provide guidance choose suitable perturbation heuristic during optimization process. A simulated annealing-like move acceptance employed determine updating incumbent domain solution prevent search from trapping into local optimum. heuristics, constructive proposed based on novel assignment rule create initial solution. Four problem-specific heuristics variable neighborhood search-based improvement operator are space. comprehensive computational experiment conducted. comparative results show that significantly outperforms Gurobi solver several closely relevant methods DHHFSP-B.

Language: Английский

Citations

40
A multi-class teaching–learning-based optimization for multi-objective distributed hybrid flow shop scheduling DOI
Deming Lei, Bin Su

Knowledge-Based Systems, Journal Year: 2023, Volume and Issue: 263, P. 110252 - 110252

Published: Jan. 10, 2023

Language: Английский

Citations

28
Toward automated algorithm configuration for distributed hybrid flow shop scheduling with multiprocessor tasks DOI
Hadi Gholami, Hongyang Sun

Knowledge-Based Systems, Journal Year: 2023, Volume and Issue: 264, P. 110309 - 110309

Published: Jan. 20, 2023

Language: Английский

Citations

28
Distributed Permutation Flow Shop Scheduling Problem with Worker flexibility: Review, trends and model proposition DOI
Tasnim Mraihi, Olfa Belkahla Driss, Hind Bril El-Haouzi

et al.

Expert Systems with Applications, Journal Year: 2023, Volume and Issue: 238, P. 121947 - 121947

Published: Oct. 10, 2023

Language: Английский

Citations

28
Scheduling stochastic distributed flexible job shops using an multi-objective evolutionary algorithm with simulation evaluation DOI
Yaping Fu, Kaizhou Gao, Ling Wang

et al.

International Journal of Production Research, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 18

Published: June 4, 2024

The trend of reverse globalisation prompts manufacturing enterprises to adopt distributed structures with multiple factories for improving production efficiency, meeting customer requirements, and responding disturbance events. This study focuses on scheduling a flexible job shop random processing time achieve minimal makespan total tardiness. First, stochastic programming model is established formulate the concerned problems. Second, in accordance natures two objectives randomness, an evolutionary algorithm incorporating evaluation method designed. In it, population-based external archive-based search processes are developed searching candidate solutions, integrates simulation discrete event calculate objective values acquired solutions. Finally, mathematical optimisation solver, CPLEX, employed validate approach. A set cases solved verify performance proposed method. comparisons discussions show superiority handling problems under study.

Language: Английский

Citations

14
A feedback learning-based selection hyper-heuristic for distributed heterogeneous hybrid blocking flow-shop scheduling problem with flexible assembly and setup time DOI
Zhongshi Shao, Weishi Shao,

Jianrui Chen

et al.

Engineering Applications of Artificial Intelligence, Journal Year: 2024, Volume and Issue: 131, P. 107818 - 107818

Published: Jan. 9, 2024

Language: Английский

Citations

11
MEDHEA: Multidimensional estimation of distribution based hyper-heuristic evolutionary algorithm for energy-efficient distributed assembly no-wait flow-shop scheduling problem DOI

Zi-Qi Zhang,

X. W. Zhu,

Yanxuan Xu

et al.

Expert Systems with Applications, Journal Year: 2025, Volume and Issue: 271, P. 126526 - 126526

Published: Jan. 30, 2025

Language: Английский

Citations

1
A network memetic algorithm for energy and labor-aware distributed heterogeneous hybrid flow shop scheduling problem DOI
Weishi Shao, Zhongshi Shao, Dechang Pi

et al.

Swarm and Evolutionary Computation, Journal Year: 2022, Volume and Issue: 75, P. 101190 - 101190

Published: Oct. 13, 2022

Language: Английский

Citations

36