A local and global search combine particle swarm optimization algorithm for job-shop scheduling to minimize makespan

DOI10.1155/2010/838596zbMath1195.90042OpenAlexW2098492828WikidataQ58650653 ScholiaQ58650653MaRDI QIDQ1958785

Zhigang Lian

Publication date: 29 September 2010

Published in: Discrete Dynamics in Nature and Society (Search for Journal in Brave)

Full work available at URL: https://eudml.org/doc/231481

Mathematics Subject Classification ID

Deterministic scheduling theory in operations research (90B35) Approximation methods and heuristics in mathematical programming (90C59)

Related Items (2)

Multi-objective two-stage multiprocessor flow shop scheduling – a subgroup particle swarm optimisation approach ⋮ Particle swarm optimization based on local attractors of ordinary differential equation system

Cites Work

• An improved GA and a novel PSO-GA-based hybrid algorithm
• A similar particle swarm optimization algorithm for job-shop scheduling to minimize makespan
• Minimizing weighted tardiness of job-shop scheduling using a hybrid genetic algorithm
• The particle swarm optimization algorithm: Convergence analysis and parameter selection
• A competitive and cooperative co-evolutionary approach to multi-objective particle swarm optimization algorithm design
• An approximate decomposition algorithm for scheduling on parallel machines with heads and tails
• A genetic algorithm applied to a classic job-shop scheduling problem
• A modification to particle swarm optimization algorithm

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