Cited by A Q-learning improved differential evolution algorithm for human-centric dynamic distributed flexible job shop scheduling problem

A Learning-Driven Multi-Objective cooperative artificial bee colony algorithm for distributed flexible job shop scheduling problems with preventive maintenance and transportation operations DOI

Zhengpei Zhang,

Yaping Fu, Kaizhou Gao

et al.

Computers & Industrial Engineering, Journal Year: 2024, Volume and Issue: 196, P. 110484 - 110484

Published: Aug. 18, 2024

Language: Английский

Citations

Hybrid quantum particle swarm optimization and variable neighborhood search for flexible job-shop scheduling problem DOI

Yuanxing Xu,

Mengjian Zhang,

Ming Yang

et al.

Journal of Manufacturing Systems, Journal Year: 2024, Volume and Issue: 73, P. 334 - 348

Published: Feb. 26, 2024

Language: Английский

Citations

Multi-objective fitness landscape-based estimation of distribution algorithm for distributed heterogeneous flexible job shop scheduling problem DOI

Fuqing Zhao, Mengjie Li, Ningning Zhu

et al.

Applied Soft Computing, Journal Year: 2025, Volume and Issue: unknown, P. 112780 - 112780

Published: Jan. 1, 2025

Language: Английский

Citations

Solving multi-objective energy-saving flexible job shop scheduling problem by hybrid search genetic algorithm DOI

L. Hao, Zhiyuan Zou, Xu Liang

et al.

Computers & Industrial Engineering, Journal Year: 2025, Volume and Issue: unknown, P. 110829 - 110829

Published: Jan. 1, 2025

Language: Английский

Citations

Quantum particle swarm optimization with chaotic encoding schemes for flexible job-shop scheduling problem DOI

Yuanxing Xu,

Deguang Wang, Mengjian Zhang

et al.

Swarm and Evolutionary Computation, Journal Year: 2025, Volume and Issue: 93, P. 101836 - 101836

Published: Jan. 7, 2025

Language: Английский

Citations

Production scheduling with multi-robot task allocation in a real industry 4.0 setting DOI

Zohreh Shakeri, Khaled Benfriha, Mohsen Varmazyar

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: Jan. 13, 2025

The demand for efficient Industry 4.0 systems has driven the need to optimize production systems, where effective scheduling is crucial. In smart manufacturing, robots handle material transfers, making precise essential seamless operations. However, research often oversimplifies Robotic Flexible Job Shop problem by focusing only on transportation time, ignoring resource allocation and robot diversity. This study addresses these gaps, tackling a Multi-Robot (MRFJS) with limited buffers. It involves non-identical parallel machines varying capabilities overseeing handling under blocking conditions. case based real scenario, layout restricts each robotic arm's access, requiring strategic buffer placement part transfers. A Mixed-Integer Programming (MILP) model aims minimize makespan, followed new Genetic Algorithm (GA) using Roy Sussman's Alternative Graph. Computational tests various scales data from manufacturing plant demonstrate GA's efficacy in solving complex problems real-world settings. Based data, Proposed (PGA), an average Relative Deviation (ARD) of 0.25%, performed approximately 34% better compared Basic (BGA), ARD 0.38%. percentage indicates that PGA significantly outperforms problems.

Language: Английский

Citations

Tabu search based on novel neighborhood structures for solving job shop scheduling problem integrating finite transportation resources DOI

Youjie Yao,

Lin Gui, Xinyu Li

et al.

Robotics and Computer-Integrated Manufacturing, Journal Year: 2024, Volume and Issue: 89, P. 102782 - 102782

Published: May 14, 2024

Language: Английский

Citations

A hybrid simheuristic algorithm for solving bi-objective stochastic flexible job shop scheduling problems DOI

Saman Nessari,

Reza Tavakkoli‐Moghaddam, Hessam Bakhshi-Khaniki

et al.

Decision Analytics Journal, Journal Year: 2024, Volume and Issue: 11, P. 100485 - 100485

Published: May 29, 2024

The flexible job shop scheduling problem (FJSSP) is a complex optimization challenge that plays crucial role in enhancing productivity and efficiency modern manufacturing systems, aimed at optimizing the allocation of jobs to variable set machines. This paper introduces an algorithm tackle FJSSP by minimizing makespan total weighted earliness tardiness under uncertainty. hybrid effectively addresses complexities stochastic multi-objective integrating equilibrium optimizer (EO) as initial solutions generator, Non-dominated sorting genetic II (NSGA-II), simulation techniques. algorithm's effectiveness validated showcasing specific instances delivering decision results for optimal across varying levels Results reveal consistent superiority managing parameters various scales, achieving lower improved Pareto front quality compared existing methods. Particularly notable faster convergence robust performance, statistical Wilcoxon test, which confirms its reliability efficacy handling dynamic situations. These findings underscore potential providing flexible, solutions. proposed unique balance exploitative explorative capabilities within framework enables effective uncertainty FJSSP, offering flexibility customization adaptable environments.

Language: Английский

Citations

Multimanned disassembly line balancing optimization considering walking workers and task evaluation indicators DOI

Tuo Yang, Zeqiang Zhang, Tengfei Wu

et al.

Journal of Manufacturing Systems, Journal Year: 2023, Volume and Issue: 72, P. 263 - 286

Published: Dec. 12, 2023

Language: Английский

Citations

An enhanced memetic algorithm with hierarchical heuristic neighborhood search for type-2 green fuzzy flexible job shop scheduling DOI

Kanglin Huang, Wenyin Gong, Chao Lu

et al.

Engineering Applications of Artificial Intelligence, Journal Year: 2023, Volume and Issue: 130, P. 107762 - 107762

Published: Dec. 26, 2023

Language: Английский

Citations