A tutorial on multiobjective optimization: fundamentals and evolutionary methods

Volume: 17, Issue: 3, Pages: 585 - 609
Published: May 31, 2018
Abstract
In almost no other field of computer science, the idea of using bio-inspired search paradigms has been so useful as in solving multiobjective optimization problems. The idea of using a population of search agents that collectively approximate the Pareto front resonates well with processes in natural evolution, immune systems, and swarm intelligence. Methods such as NSGA-II, SPEA2, SMS-EMOA, MOPSO, and MOEA/D became standard solvers when it comes...
Paper Details
Title
A tutorial on multiobjective optimization: fundamentals and evolutionary methods
Published Date
May 31, 2018
Volume
17
Issue
3
Pages
585 - 609
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