Improving multi-objective algorithms performance by emulating behaviors from the human social analogue in candidate solutions

DOI10.1016/j.ejor.2020.11.028zbMath1487.90591OpenAlexW3107730271MaRDI QIDQ2030476

Konstantinos Metaxiotis, Konstantinos Liagkouras

Publication date: 7 June 2021

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

Full work available at URL: https://doi.org/10.1016/j.ejor.2020.11.028

zbMATH Keywords

metaheuristicsevolutionary algorithmsindividualsbiological analoguecandidate solutions

Mathematics Subject Classification ID

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

Related Items (1)

Constrained multi-objective optimization of compact microwave circuits by design triangulation and Pareto front interpolation

Uses Software

• Genocop
• MOEA/D
• SPEA2
• SMS-EMOA
• Omni-optimizer

Cites Work

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• Multi-objective evolutionary algorithms for a reliability location problem
• An analysis of the hypervolume Sharpe-ratio indicator
• Omni-optimizer: a generic evolutionary algorithm for single and multi-objective optimization
• The Oxford Handbook of Panel Data

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