An interactive fuzzy satisficing method for multiobjective nonconvex programming problems through floating point genetic algorithms

DOI10.1016/S0377-2217(98)00128-3zbMath0998.90073OpenAlexW2045286136MaRDI QIDQ1847151

Katsuhiro Yauchi, Masatoshi Sakawa

Publication date: 17 November 2002

Published in: European Journal of Operational Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0377-2217(98)00128-3

zbMATH Keywords

genetic algorithmsinteractive methodsfuzzy goalsmultiobjective nonconvex programming problemsfloating pointrepresentation

Mathematics Subject Classification ID

Nonconvex programming, global optimization (90C26) Multi-objective and goal programming (90C29)

Related Items (9)

Experiments with classification-based scalarizing functions in interactive multiobjective optimization ⋮ A new genetic algorithm for solving nonconvex nonlinear programming problems ⋮ An approach for solving a fuzzy multiobjective programming problem ⋮ A multi-objective optimization evolutionary algorithm incorporating preference information based on fuzzy logic ⋮ A multi-item multi-objective inventory model in exponential fuzzy environment using chance-operator techniques ⋮ Multi-objective meta-heuristics: An overview of the current state-of-the-art ⋮ A multi-objective joint replenishment inventory model of deteriorated items in a fuzzy environment ⋮ A sixth bibliography of fractional programming ⋮ Interactive fuzzy programming for two-level nonconvex programming problems with fuzzy parameters through genetic algorithms

Uses Software

• Genocop

Cites Work

• Interactive fuzzy decision making for multiobjective nonlinear programming using augmented minimax problems
• Interactive fuzzy decision-making for multi-objective nonlinear programming using reference membership intervals
• An interactive fuzzy satisficing method using augmented minimax problems and its application to environmental systems
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