Hybrid social spider optimization algorithm with differential mutation operator for the job-shop scheduling problem

DOI10.3934/jimo.2019122zbMath1476.90293OpenAlexW2981514168MaRDI QIDQ2031353

Ruxin Zhao, Guo Zhou, Yongquan Zhou

Publication date: 9 June 2021

Published in: Journal of Industrial and Management Optimization (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.3934/jimo.2019122

zbMATH Keywords

job-shop schedulingmetaheuristic optimizationsocial spider optimizationdifferential mutation operator

Mathematics Subject Classification ID

Deterministic scheduling theory in operations research (90B35) Combinatorial optimization (90C27)

Uses Software

• OR-Library

Cites Work

• A tabu search/path relinking algorithm to solve the job shop scheduling problem
• An effective new island model genetic algorithm for job shop scheduling problem
• Scheduling open shops with parallel machines to minimize total completion time
• A simulated annealing algorithm based on block properties for the job shop scheduling problem with total weighted tardiness objective
• Differential evolution -- a simple and efficient heuristic for global optimization over continuous spaces
• A guided local search with iterative ejections of bottleneck operations for the job shop scheduling problem
• A new hybrid genetic algorithm for job shop scheduling problem
• Deterministic job-shop scheduling: Past, present and future
• A hybrid evolutionary algorithm for the job shop scheduling problem
• Exact, Heuristic and Meta-heuristic Algorithms for Solving Shop Scheduling Problems

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