Portfolio Optimization with Translation of Representation for Transport Problems

Malgorzata ZAJECKA, Mateusz MASTALERCZYK, Siang Yew CHONG, Xin YAO, Joanna KWIECIEN, Wojciech CHMIEL, Jacek DAJDA, Marek KISIEL-DOROHINICKI, Aleksander BYRSKI*

*Corresponding author for this work

Research output: Journal PublicationsJournal Article (refereed)peer-review

Abstract

The paper presents a hybridization of two ideas closely related to metaheuristic computing, namely Portfolio Optimization (researched by Xin Yao et al.) and Translation of Representation for different metaheuristics (researched by Byrski et al.). Thus, difficult problems (discrete optimization) are approached by a sequential run through a number of steps of different metaheuristics, providing the translation of representation (since the algorithms are completely different). Therefore, close cooperation of e.g. ACO, PSO, and GAis possible. The results refer to unaltered algorithms and show the superiority of the constructed hybrid.
Original languageEnglish
Pages (from-to)57-75
JournalJournal of Artificial Intelligence and Soft Computing Research
Volume15
Issue number1
Early online date8 Dec 2024
DOIs
Publication statusPublished - Jan 2025

Keywords

  • metaheuristics
  • portfolio optimization
  • transport problems

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