A web-based interactive decision support system for a multi-objective lot-sizing and production scheduling model

Yannik Zeiträg, José Rui Figueira and Miguel Alves Pereira

International Journal of Production Economics, 2024, vol. 271, issue C

Abstract: In the course of globalization and the corresponding steadily growing market dynamics, companies are faced with an increasing challenge to remain competitive. Therefore, the efficient use of the available resources, while maintaining a high level of service and customer satisfaction, is a key instrument for ensuring success. Within this framework, production scheduling can be seen as one of the most decisive operational activities of a manufacturing company, with the production orders being sequenced in a way that allows the achievement of an efficient allocation of the available resources. Furthermore, the correlated lot-sizing represents a crucial influencing factor in production scheduling. In this article, a novel methodology to solve multi-objective lot-sizing and production scheduling problems is proposed. Essentially, it provides an interactive three-phase framework that supports a procedure for simultaneous decision-making regarding lot-sizing and production scheduling. The main goal is not only to find an appropriate production schedule that best meets the decision-maker’s preferences but also to gain a deeper insight into the relationship among criteria and a better understanding of possible trade-offs between competing objectives. To guide the user through the whole decision-making process, a web-based interactive application was developed. The proposed methodology was applied to a case study regarding an automotive supplier company, revealing itself as a viable and practical technique able to solve real-world multi-objective lot-sizing and production scheduling problems in the manufacturing industry.

Keywords: Multiple objective programming; Decision support systems; Lot-sizing; Production scheduling; Web-based platform (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:proeco:v:271:y:2024:i:c:s0925527324000665

DOI: 10.1016/j.ijpe.2024.109209

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