Volume 56, Number 4, July-August 2022
|Page(s)||3187 - 3217|
|Published online||05 September 2022|
Evaluating process flexibility in lot sizing problems: an approach based on multicriteria decision making
School of Applied Sciences, University of Campinas, R. Pedro Zaccaria, 1300, Limeira São Paulo 13484-350, Brazil
Accepted: 2 August 2022
This paper presents a multicriteria analysis of the process flexibility in the context of the lot sizing problem with parallel machines. In the standard design for lot sizing problems, each machine can manufacture all products (total or complete flexibility). However, installing machines with complete flexibility for several practical applications can be costly. Therefore, it becomes interesting to implement only a limited amount of machine flexibility, where each machine can produce only a small number of different products. Recently, some works presented analyses of process flexibility by considering only the production cost as a criterion. However, the literature lacks a more comprehensive analysis that considers other essential criteria regarding the problem to compute the value of a flexibility configuration. Thus, we provide a detailed multicriteria analysis based on the TOPSIS method that produces a ranking of alternatives for the flexibility configurations. Extensive computational experiments and sensitivity analyses for different scenarios of the lot sizing problem compare individual flexibility configurations and evaluate its advantages in manufacturing planning. The computational results showed that limited flexibility configurations outperform the total flexibility in all scenarios. Moreover, different from the studies considering only the total cost as the criterion, investing in flexibility for all capacity levels has advantages.
Mathematics Subject Classification: 90-05 / 90-08 / 90-10
Key words: Lot sizing problems / process flexibility / multicriteria analysis / TOPSIS method
© The authors. Published by EDP Sciences, ROADEF, SMAI 2022
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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