4.7 Article

An extended goal programming model for the multiobjective integrated lot-sizing and cutting stock problem

Journal

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
Volume 295, Issue 3, Pages 996-1007

Publisher

ELSEVIER
DOI: 10.1016/j.ejor.2021.03.049

Keywords

Goal programming; Lot-sizing problems; Cutting-stock problems; Integrated problems; Extended goal programming

Funding

  1. Fundacao de Amparo aPesquisa do Estado de Sao Paulo (FAPESP) [2016/01860-1, 2018/18754-5]
  2. FAEPEX-Unicamp [3390/17]

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This paper introduces a new extended goal programming model for the integrated lot-sizing and cutting stock problem, which considers multiple criteria from different stakeholders in the manufacturing process. The model allows for balancing conflicting goals of multiple stakeholders and cost efficiency. A column generation-based heuristic procedure is applied to efficiently solve the proposed model.
Lot sizing and cutting stock problems generally arise in manufacturing as a two stage connected process. Although these two problems have been addressed separately by many authors, recently, inspired by practical applications, some studies have emerged analyzing their integration. The mono-objective version of the integrated lot-sizing and cutting stock problem can be considered as an enhancement that minimizes the global production cost. However, it does not include the multiple criteria that can arise from the inclusion of multiple stakeholders in a modern, distributed manufacturing process. This paper aims to introduce a new extended goal programming model for the integrated lot-sizing and cutting stock problem which models the arising multiple criteria by a set of goals representing the interests of different stakeholders in the manufacturing process. This formulation allows for the consideration of the balance between the conflicting goals of multiple stakeholders and the cost efficiency of the overall process. In order to efficiently solve the proposed model, a column generation based heuristic procedure is applied. The trade-offs among the various criteria related to the problem are assessed, and a series of computational experiments are performed. The computational results compare individual criteria weighting schemes and evaluate the goals' sensitivity using performance profiles and time-to-target plots methodologies. (c) 2021 Elsevier B.V. All rights reserved.

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