Optimal product design using conjoint analysis: Computational complexity and algorithms
type: Item
instance of: scholarly article
title: Optimal product design using conjoint analysis: Computational complexity and algorithms
zbMATH Open document ID: 0663.90053
DOI: 10.1016/0377-2217(89)90329-9
author: Rajeev Kohli
author: Ramesh Krishnamurti
published in: European Journal of Operational Research
publication date: 1989-01-01T00:00:00Z
review text: The problem of maximizing the share of a new product introduced in a competitive market is shown to be NP-hard. A directed graph representation of the problem is used to construct shortest path and dynamic programming heuristics. Both heuristics are shown to have arbitrarily bad worst-case bounds. Computational experience with real- sized problems is reported. Both heuristics identify near-optimal solutions for the simulated problems, the dynamic programming heuristic performing better than the shortest path heuristic.
Mathematics Subject Classification ID: 90B99
Mathematics Subject Classification ID: 68Q25
zbMATH DE Number: 4085409
zbMATH Keywords: optimal product design
zbMATH Keywords: marketing
zbMATH Keywords: conjoint analysis
zbMATH Keywords: NP-hard
zbMATH Keywords: dynamic programming heuristics
zbMATH Keywords: worst-case
zbMATH Keywords: shortest path heuristic
MaRDI profile type: Publication
full work available at URL: 0377-2217(89)90329-9
OpenAlex ID: W2007317506
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description: scientific article; zbMATH DE number 4085409