Optimal product design using a colony of virtual ants

Optimal product design using a colony of virtual ants

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Article ID: iaor20084231
Country: Netherlands
Volume: 176
Issue: 1
Start Page Number: 498
End Page Number: 520
Publication Date: Jan 2007
Journal: European Journal of Operational Research
Authors: ,
Keywords: combinatorial optimization, heuristics: ant systems
Abstract:

The optimal product design problem, where the ‘best’ mix of product features are formulated into an ideal offering, is formulated using ant colony optimization (ACO). Here, algorithms based on the behavior of social insects are applied to a consumer decision model designed to guide new product decisions and to allow planning and evaluation of product offering scenarios. ACO heuristics are efficient at searching through a vast decision space and are extremely flexible when model inputs continuously change. When compared to complete enumeration of all possible solutions, ACO is found to generate near-optimal results for this problem. Prior research has focused primarily on optimal product planning using consumer preference data from a single point in time. Extant literature suggests these formulations are overly simplistic, as a consumer's level of preference for a product is affected by past experience and prior choices. This application models consumer preferences as evolutionary, shifting over time.

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