Heuristics for product-line design using conjoint analysis
Management Science
An introduction to genetic algorithms
An introduction to genetic algorithms
Genetic algorithms for product design
Management Science
A genetic algorithm for the generalised assignment problem
Computers and Operations Research
Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control and Artificial Intelligence
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Order acceptance with weighted tardiness
Computers and Operations Research
Order acceptance using genetic algorithms
Computers and Operations Research
Expert Systems with Applications: An International Journal
An approach to competitive product line design using conjoint data
Expert Systems with Applications: An International Journal
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In this paper an evolutionary algorithm (EA) approach for solving the share of choices problem in the design of a line of substitute products is presented. Because this problem is NP-hard, we are forced to use heuristic methods, which do not guarantee obtaining the optimal solution. In order to see whether there exists any computational advantage of the EA approach, it is compared to the beam search (BS) heuristic method. An extensive comparative computational study is performed. The solutions found by the EA are close to optimal. Moreover, in most cases the EA obtains a better solution than that found by the BS method. In most problem sizes the BS method is faster than the EA. However, the CPU time needed by the EA is very reasonable. Moreover, the EA can be used as an effective second step to the BS method.