MEMOTS: a memetic algorithm integrating tabu search for combinatorial multiobjective optimization

DOI10.1051/ro:2008003zbMath1170.90479OpenAlexW2124090520MaRDI QIDQ5456580

Thibaut Lust, Jacques jun. Teghem

Publication date: 8 April 2008

Published in: RAIRO - Operations Research (Search for Journal in Brave)

Full work available at URL: https://eudml.org/doc/105390

zbMATH Keywords

tabu searchmemetic algorithmhybrid metaheuristicKnapsackcombinatorial multiobjective optimization

Mathematics Subject Classification ID

Multi-objective and goal programming (90C29) Approximation methods and heuristics in mathematical programming (90C59)

Related Items (6)

Multi- and many-objective path-relinking: a taxonomy and decomposition approach ⋮ An improved version of a core based algorithm for the multi-objective multi-dimensional knapsack problem: a computational study and comparison with meta-heuristics ⋮ Greedy algorithms for a class of knapsack problems with binary weights ⋮ Unnamed Item ⋮ MEMOTS ⋮ The multiobjective multidimensional knapsack problem: a survey and a new approach

Uses Software

• PAES
• Tabu search

Cites Work

• Unnamed Item
• Unnamed Item
• A comparative study of multiple-objective metaheuristics on the bi-objective set covering problem and the Pareto memetic algorithm
• The Pareto fitness genetic algorithm: test function study
• System optimization of turbofan engines using genetic algorithms
• Multiple criteria optimization: State of the art annotated bibliographic surveys
• Metaheuristics for multiobjective optimisation
• 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
• Genetic local search for multi-objective combinatorial optimization

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