Solving multiobjective optimization problems using artificial bee colony algorithm

DOI10.1155/2011/569784zbMath1233.90254OpenAlexW2061428286WikidataQ56740750 ScholiaQ56740750MaRDI QIDQ764557

Yunlong Zhu, Wenping Zou, Beiwei Zhang, Hanning Chen

Publication date: 13 March 2012

Published in: Discrete Dynamics in Nature and Society (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1155/2011/569784

Mathematics Subject Classification ID

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

Related Items (4)

Design of variable elliptical filters with direct tunability in 2D domain ⋮ A developed artificial bee colony algorithm based on cloud model ⋮ Augmented Lagrangian cone method for multiobjective optimization problems with an application to an optimal control problem ⋮ A novel algorithm to scheduling optimization of melting-casting process in copper alloy strip production

Uses Software

• MOEA/D
• SPEA2
• ABC
• MOPSO

Cites Work

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• Intelligent control and optimization under uncertainty with application to hydro power
• A comparative study of artificial bee colony algorithm
• A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm
• Hybrid Particle Swarm Optimizers in the Single Machine Scheduling Problem: An Experimental Study
• Comprehensive learning particle swarm optimizer for solving multiobjective optimization problems
• Nonlinear goal programming using multi-objective genetic algorithms
• On the Arnold conjecture and the Atiyah-Patodi-Singer index theorem.

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