Multiobjective cloud particle optimization algorithm based on decomposition

DOI10.3390/a8020157zbMath1461.90141OpenAlexW2086391932MaRDI QIDQ1736646

Qiaoyong Jiang, Wei Li, Bin Wang, Lei Wang, Xinhong Hei

Publication date: 26 March 2019

Published in: Algorithms (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.3390/a8020157

zbMATH Keywords

multiobjective optimizationevolutionary algorithmMOEA/Dcloud mutationcloud particle differential evolution

Mathematics Subject Classification ID

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

Related Items (4)

Loser-out multi metaheuristic framework for multi-objective optimization ⋮ An improved MOEA/D with optimal DE schemes for many-objective optimization problems ⋮ Algorithms for managing, querying and processing big data in cloud environments ⋮ Evolutionary search with multiple utopian reference points in decomposition-based multiobjective optimization

Uses Software

• MOEA/D
• SMS-EMOA

Cites Work

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• MOEA/D + uniform design: a new version of MOEA/D for optimization problems with many objectives
• Survey of multi-objective optimization methods for engineering
• A multiobjective evolutionary algorithm based on decomposition with normal boundary intersection for traffic grooming in optical networks
• SMS-EMOA: multiobjective selection based on dominated hypervolume
• Information processing with evolutionary algorithms. From industrial applications to academic speculations.
• A Scatter Search Approach for Solving the Automatic Cell Planning Problem
• A survey of simulated annealing as a tool for single and multiobjective optimization
• The Multiobjective Traveling Salesman Problem: A Survey and a New Approach

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