Clonal Selection Algorithms for Optimal Product Line Design
| Autor: | Konstantinos Zervoudakis, Vasiliki Ntamadaki, Michail Pantourakis, Stelios Tsafarakis, Andreas Andronikidis, Efthymios Altsitsiadis |
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| Jazyk: | angličtina |
| Rok vydání: | 2022 |
| Předmět: |
Information Systems and Management
Combinatorial optimization General Computer Science Product design Computer science business.industry Clonal selection algorithm Context (language use) Management Science and Operations Research Or in marketing Industrial and Manufacturing Engineering Product line design Modeling and Simulation Simulated annealing Genetic algorithm Local search (optimization) business Algorithm Selection (genetic algorithm) |
| Zdroj: | European Journal of Operational Research. 298(2):585-595 |
| ISSN: | 1872-6860 0377-2217 |
| DOI: | 10.1016/j.ejor.2021.07.006 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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