Optimal product line design: Genetic algorithm approach to mitigate cannibalization

Optimal product line design: Genetic algorithm approach to mitigate cannibalization

0.00 Avg rating0 Votes
Article ID: iaor20072148
Country: Netherlands
Volume: 131
Issue: 2
Start Page Number: 227
End Page Number: 244
Publication Date: Nov 2006
Journal: Journal of Optimization Theory and Applications
Authors: , ,
Keywords: heuristics: genetic algorithms
Abstract:

In this marketing-oriented era where manufacturers maximize profits through customer satisfaction, there is an increasing need to design a product line rather than a single product. By offering a product line, the manufacturer can customize his or her products to the needs of a variety of segments in order to maximize profits by satisfying more customers than a single product would. When the amount of data on customer preferences or possible product configurations is large and no analytical relations can be established, the problem of an optimal product line design becomes very difficult and there are no traditional methods to solve it. In this paper, we show that the usage of genetic algorithms, a mathematical heuristics mimicking the process of biological evolution, can solve efficiently the problem. Special domain operators were developed to help the genetic algorithm mitigate cannibalization and enhance the algorithm's local search abilities. Using manufacturer's profits as the criterion for fitness in evaluating chromosomes, the usage of domain specific operators was found to be highly beneficial with better final results. Also, we have hybridized the genetic algorithm with a linear programming postprocessing step to fine tune the prices of products in the product line. Attacking the core difficulty of cannibalization in the algorithm, the operators introduced in this work are unique.

Reviews

Required fields are marked *. Your email address will not be published.