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A Heuristic Genetic Algorithm for Product Portfolio Planning by Jianxin (Roger) Jiao; Yiyang Zhang; Yi Wang is a Engineering article available to read on EtoBox.

What is A Heuristic Genetic Algorithm for Product Portfolio Planning about?

Product portfolio planning has been recognized as a critical decision facing all companies across industries. It aims at the selection of a near-optimal mix of products and attribute levels to offer in the target market. It constitutes a combinatorial optimization problem that is deemed to be NP-hard in nature. Conventional enumeration-based optimization techniques become inhibitive given that the number of possible combinations may be enormous. Genetic algorithms have been proven to excel in solving combinatorial optimization problems. This paper develops a heuristic genetic algorithm for solving the product portfolio planning problem more effectively. A generic encoding scheme is introduced to synchronize product portfolio generation and selection coherently. The fitness function is established based on a shared surplus measure leveraging both the customer and engineering concerns. An unbalanced index is proposed to model the elitism of product portfolio solutions.

Who reads A Heuristic Genetic Algorithm for Product Portfolio Planning?

Author

Jianxin (Roger) Jiao; Yiyang Zhang; Yi Wang

Publisher

Elsevier Science; Elsevier ; Elsevier Ltd.; Elsevier BV (ISSN 0305-0548)

Published

2007

Language

EN

Field

Engineering (Physical Sciences)