Pareto-ranking based quantum-behaved particle swarm optimization for multiobjective optimization
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Publication:1667014
DOI10.1155/2015/940592zbMath1394.90582OpenAlexW1565353536WikidataQ59120355 ScholiaQ59120355MaRDI QIDQ1667014
Publication date: 27 August 2018
Published in: Mathematical Problems in Engineering (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1155/2015/940592
Approximation methods and heuristics in mathematical programming (90C59) Quantum computation (81P68)
Related Items (2)
A novel memetic algorithm based on decomposition for multiobjective flexible job shop scheduling problem ⋮ A novel multiobjective quantum-behaved particle swarm optimization based on the ring model
Cites Work
- A novel strategy of Pareto-optimal solution searching in multi-objective particle swarm optimization (MOPSO)
- Pareto-optimality approach for flexible job-shop scheduling problems: Hybridization of evolutionary algorithms and fuzzy logic
- Routing and scheduling in a flexible job shop by tabu search
- A hybrid genetic and variable neighborhood descent algorithm for flexible job shop scheduling problems
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