Fuzzy Self-Tuning Differential Evolution for Optimal Product Line Design

Stelios Tsafarakis*, Konstantinos Zervoudakis, Andreas Andronikidis, Efthymios Altsitsiadis

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

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Designing a successful product line is a critical decision for a firm to stay competitive. By offering a line of products, the manufacturer can maximize profits or market share through satisfying more consumers than a single product would. The optimal Product Line Design (PLD) problem is classified as NP-hard. This paper proposes a Fuzzy Self-Tuning Differential Evolution (FSTDE) for PLD, which exploits Fuzzy Logic to automatically calculate the parameters independently for each solution during the optimization, thus resulting to a settings-free version of DE. The proposed method is compared to the most successful mutation strategies of the algorithm as well as previous approaches to the PLD problem, like Genetic Algorithm and Simulated Annealing, using both actual and artificial data of consumer preferences. The comparison results demonstrate that FSTDE is an attractive alternative approach to the PLD problem.
Original languageEnglish
JournalEuropean Journal of Operational Research
Issue number3
Pages (from-to)1161-1169
Number of pages9
Publication statusPublished - Dec 2020

Bibliographical note

Published online: 23 May 2020


  • Differential evolution
  • Fuzzy logic
  • OR in marketing
  • Product line design
  • Self-tuning

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