Interactive Multiobjective Optimization in Lot Sizing with Safety Stock and Safety Lead Time
Kania, A., Sipilä, J., Afsar, B., & Miettinen, K. (2021). Interactive Multiobjective Optimization in Lot Sizing with Safety Stock and Safety Lead Time. In M. Mes, E. Lalla-Ruiz, & S. Voß (Eds.), Computational Logistics : 12th International Conference, ICCL 2021, Enschede, The Netherlands, September 27–29, 2021, Proceedings (pp. 208-221). Springer. Lecture Notes in Computer Science, 13004. https://doi.org/10.1007/978-3-030-87672-2_14
Published inLecture Notes in Computer Science
Embargoed until: 2022-09-22Request copy from author
© Springer Nature Switzerland AG 2021
In this paper, we integrate a lot sizing problem with the problem of determining optimal values of safety stock and safety lead time. We propose a probability of product availability formula to assess the quality of safety lead time and a multiobjective optimization model as an integrated lot sizing problem. In the proposed model, we optimize six objectives simultaneously: minimizing purchasing cost, ordering cost, holding cost and, at the same time, maximizing cycle service level, probability of product availability and inventory turnover. To present the applicability of the proposed model, we consider a real case study with data from a manufacturing company and apply the interactive NAUTILUS Navigator method to support the decision maker from the company to find his most preferred solution. In this way, we demonstrate how the decision maker navigates without having to trade-off among the conflicting objectives and could find a solution that reflects his preference well.
Parent publication ISBN978-3-030-87671-5
ConferenceInternational Conference on Computational Logistics
Is part of publicationComputational Logistics : 12th International Conference, ICCL 2021, Enschede, The Netherlands, September 27–29, 2021, Proceedings
Publication in research information system
MetadataShow full item record
Related funder(s)Academy of Finland
Funding program(s)Research profiles, AoF; Academy Project, AoF
Additional information about fundingThis research was partly funded by LPDP, the Indonesian Endowment Fund for Education (grant number S-5302/LPDP.4/2020), and the Academy of Finland (grants 322221 and 311877). The research is related to the thematic research area DEMO (Decision Analytics utilizing Causal Models and Multiobjective Optimization, jyu.fi/demo) of the University of Jyväskylä.
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