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Agent-based optimization for product family design

Author

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  • Rahul Rai
  • Venkat Allada

Abstract

This paper presents a two-step approach to determine the optimal platform level for a selected set of product families and their variants. The first step employs a multi-objective optimization using an agent-based framework to determine the Pareto-design solutions for a given set of modules. The second step performs a post optimization analysis that includes application of the quality loss function (QLF) to determine the optimal platform level. The post optimization analysis yields the optimal platform level for a related set of product families and their variants. We demonstrate the working of the proposed method by using an example problem. Copyright Springer Science + Business Media, Inc. 2006

Suggested Citation

  • Rahul Rai & Venkat Allada, 2006. "Agent-based optimization for product family design," Annals of Operations Research, Springer, vol. 143(1), pages 147-156, March.
    • Handle: RePEc:spr:annopr:v:143:y:2006:i:1:p:147-156:10.1007/s10479-006-7378-x
    DOI: 10.1007/s10479-006-7378-x
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    Cited by:

    1. Stelios Tsafarakis, 2016. "Redesigning product lines in a period of economic crisis: a hybrid simulated annealing algorithm with crossover," Annals of Operations Research, Springer, vol. 247(2), pages 617-633, December.
    2. Victor Dragotă & Camelia Delcea, 2019. "How Long Does It Last to Systematically Make Bad Decisions? An Agent-Based Application for Dividend Policy," JRFM, MDPI, vol. 12(4), pages 1-34, November.
    3. Haluk Yoeruer, 2020. "The Role of Platform Architecture Characteristics in Flexible Decision-Making," International Journal of Innovation and Technology Management (IJITM), World Scientific Publishing Co. Pte. Ltd., vol. 16(08), pages 1-28, January.

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