An Investigation into Many-objective Optimization Problems: A Case Study of the Dial-a-Ride Problem

Renan Jose Dos Santos Viana, Flavio Vinicius Cruzeiro Martins, Elizabeth Fialho Wanner

Research output: Contribution to journalArticlepeer-review

Abstract

Multi-objective optimization problems with more than three objectives are commonly referred to as many-objective optimization problems. Usually, this class of problem brings new and complex challenges to the current optimization methods, mainly maintaining the right balance between convergence and diversity. During the last years, various approaches have been proposed to solve many-objective problems. However, most existing experimental comparative studies are restricted to continuous problems. Few studies have encompassed the most recently proposed state-of-the-art approaches and made an experimental comparison applied to combinatorial optimization problems. Aiming to fill this gap, this paper presents a comparative analysis with eight algorithms covering various categories to solve a many-objective Dial-a-Ride problem. The results show that different observations can be made about the algorithms' behavior when using different test sets. Also, algorithms originally proposed to deal with problems with up to three objectives have overcome recently proposed ones.
Original languageSpanish
Pages (from-to)73-81
JournalIEEE Latin America Transactions
Volume20
Issue number1
Early online date23 Dec 2021
DOIs
Publication statusPublished - Jan 2022

Keywords

  • Optimization, IEEE transactions, Evolutionary computation, Public transportation, Optimization methods, Laser radar, Indexes
  • Many-objective optimization, dial-a-ride problem, multi-objective evolutionary algorithms, combinatorial optimization

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