Fuzzy Self-Tuning Differential Evolution for Optimal Product Line Design

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

*Corresponding author af dette arbejde

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

Abstrakt

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.
OriginalsprogEngelsk
TidsskriftEuropean Journal of Operational Research
Vol/bind287
Udgave nummer3
Sider (fra-til)1161-1169
Antal sider9
ISSN0377-2217
DOI
StatusUdgivet - dec. 2020

Bibliografisk note

Published online: 23 May 2020

Emneord

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

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