articleIEEE Transactions on Evolutionary ComputationJan 1, 2016Closed access

A Survey of Multiobjective Evolutionary Algorithms based on Decomposition

National University of Singapore · Jadavpur University

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Abstract

Decomposition is a well-known strategy in traditional multiobjective optimization. However, the decomposition strategy was not widely employed in evolutionary multiobjective optimization until Zhang and Li proposed multiobjective evolutionary algorithm based on decomposition (MOEA/D) in 2007. MOEA/D proposed by Zhang and Li decomposes a multiobjective optimization problem into a number of scalar optimization subproblems and optimizes them in a collaborative manner using an evolutionary algorithm (EA). Each subproblem is optimized by utilizing the information mainly from its several neighboring subproblems. Since the proposition of MOEA/D in 2007, decomposition-based MOEAs have attracted significant attention…

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Authors

4

Topics & keywords

Keywords
  • Evolutionary algorithm
  • Multi-objective optimization
  • Decomposition
  • Mathematical optimization
  • Evolutionary computation
  • Optimization problem
  • Computer science
  • Selection (genetic algorithm)
UN Sustainable Development Goals
  • Peace, Justice and strong institutions
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