On operators and search space topology in multi-objective flow shop scheduling
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Publication:872256
DOI10.1016/j.ejor.2006.06.010zbMath1121.90057OpenAlexW2135035157MaRDI QIDQ872256
Publication date: 27 March 2007
Published in: European Journal of Operational Research (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.ejor.2006.06.010
Search theory (90B40) Management decision making, including multiple objectives (90B50) Deterministic scheduling theory in operations research (90B35)
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Uses Software
Cites Work
- The application of the simulated annealing algorithm to the solution of the \(n/m/C_{\max}\) flowshop problem
- Landscapes, operators and heuristic search
- Benchmarks for shop scheduling problems
- A new adaptive multi-start technique for combinatorial global optimizations
- Metaheuristics for multiobjective optimisation
- An efficient genetic algorithm for job shop scheduling with tardiness objectives.
- Solving multi-objective production scheduling problems using metaheuristics
- A combined branch-and bound and genetic algorithm based approach for a flowshop scheduling problem
- Benchmarks for basic scheduling problems
- Optimization and Approximation in Deterministic Sequencing and Scheduling: a Survey
- Pareto simulated annealing—a metaheuristic technique for multiple‐objective combinatorial optimization
- MOSA method: a tool for solving multiobjective combinatorial optimization problems
- Evolutionary Multi-Criterion Optimization
- Evolutionary Multi-Criterion Optimization
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