Clonal Selection Algorithms for Optimal Product Line Design: A Comparative Study

Michail Pantourakis, Stelios Tsafarakis*, Konstantinos Zervoudakis*, Efthymios Altsitsiadis*, Andreas Andronikidis*, Vasiliki Ntamadaki

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

Abstract

Product design constitutes a critical process for a firm to stay competitive. Whilst the biologically inspired Clonal Selection Algorithms (CSA) have been applied to efficiently solve several combinatorial optimization problems, they have not yet been tested for optimal product lines. By adopting a previous comparative analysis with real and simulated conjoint data, we adapt and compare in this context 23 CSA variants. Our comparison demonstrates the efficiency of specific cloning, selection and somatic hypermutation operators against other optimization algorithms, such as Simulated Annealing and Genetic Algorithm. To further investigate the robustness of each method to combinatorial size, we extend the previous paradigm to larger product lines and different optimization objectives. The consequent performance variation elucidates how each operator shifts the search focus of CSAs. Collectively, our study demonstrates the importance of a fine balance between global and local search in such combinatorial problems, and the ability of CSAs to achieve it.
Original languageEnglish
JournalEuropean Journal of Operational Research
Number of pages11
ISSN0377-2217
DOIs
Publication statusPublished - 10 Jul 2021

Bibliographical note

Epub ahead of print. Published online: 10 July 2021.

Keywords

  • Or in marketing
  • Clonal selection algorithm
  • Combinatorial optimization
  • Product line design

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