Optimal product design using a colony of virtual ants

David Albritton, Patrick R. McMullen

Research output: Contribution to journalArticle

51 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)498-520
Number of pages23
JournalEuropean Journal of Operational Research
Volume176
Issue number1
DOIs
StatePublished - Jan 1 2007

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Keywords

  • Ant colony optimization (ACO)
  • Combinatorial optimization
  • Heuristics
  • Product design/planning
  • Swarm intelligence (SI)

ASJC Scopus subject areas

  • Information Systems and Management
  • Management Science and Operations Research
  • Statistics, Probability and Uncertainty
  • Applied Mathematics
  • Modeling and Simulation
  • Transportation

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