articleIEEE Transactions on Evolutionary ComputationJan 24, 2022GREEN OA

An Evolutionary Multitasking Optimization Framework for Constrained Multiobjective Optimization Problems

Zhengzhou University · Zhongyuan University of Technology · +1 more institution

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Abstract

When addressing constrained multiobjective optimization problems (CMOPs) via evolutionary algorithms, various constraints and multiple objectives need to be satisfied and optimized simultaneously, which causes difficulties for the solver. In this article, an evolutionary multitasking (EMT)-based constrained multiobjective optimization (EMCMO) framework is developed to solve CMOPs. In EMCMO, the optimization of a CMOP is transformed into two related tasks: one task is for the original CMOP, and the other task is only for the objectives by ignoring all constraints. The main purpose of the second task is to continuously provide useful knowledge of objectives to the first task, thus facilitating solving the CMOP.…

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252
total citations
FWCI
35.79
Percentile
100%
References
59
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Authors

6

Topics & keywords

Keywords
  • Human multitasking
  • Computer science
  • Benchmark (surveying)
  • Evolutionary algorithm
  • Task (project management)
  • Multi-objective optimization
  • Solver
  • Mathematical optimization
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