articleIEEE Transactions on Evolutionary ComputationJul 12, 2016Closed access

Performance of Decomposition-Based Many-Objective Algorithms Strongly Depends on Pareto Front Shapes

HIHisao IshibuchiYSYu SetoguchiHMHiroyuki MasudaYNYusuke Nojima

Osaka Prefecture University

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Abstract

Recently, a number of high performance many-objective evolutionary algorithms with systematically generated weight vectors have been proposed in the literature. Those algorithms often show surprisingly good performance on widely used DTLZ and WFG test problems. The performance of those algorithms has continued to be improved. The aim of this paper is to show our concern that such a performance improvement race may lead to the overspecialization of developed algorithms for the frequently used many-objective test problems. In this paper, we first explain the DTLZ and WFG test problems. Next, we explain many-objective evolutionary algorithms characterized by the use of systematically generated weight vectors.…

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Topics & keywords

Topics
Keywords
  • Evolutionary algorithm
  • Sorting
  • Multi-objective optimization
  • Algorithm
  • Weight
  • Pareto principle
  • Computer science
  • Evolutionary computation
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