Integration of lot sizing and safety strategy placement using interactive multiobjective optimization
Kania, A., Sipilä, J., Misitano, G., Miettinen, K., & Lehtmäki, J. (2022). Integration of lot sizing and safety strategy placement using interactive multiobjective optimization. Computers and Industrial Engineering, 173, Article 108731. https://doi.org/10.1016/j.cie.2022.108731
Julkaistu sarjassa
Computers and Industrial EngineeringPäivämäärä
2022Oppiaine
Multiobjective Optimization GroupLaskennallinen tiedePäätöksen teko monitavoitteisestiMultiobjective Optimization GroupComputational ScienceDecision analytics utilizing causal models and multiobjective optimizationTekijänoikeudet
© 2022 The Authors. Published by Elsevier Ltd.
We address challenges of unpredicted demand and propose a multiobjective optimization model to integrate a lot sizing problem with safety strategy placement and optimize conflicting objectives simultaneously. The novel model is devoted to a single-item multi-period problem in periodic review policy. As a safety strategy, we use the traditional safety stock concept and a novel concept of safety order time, which uses a time period to determine the additional stock to handle demand uncertainty. The proposed model has four objective functions: purchasing and ordering cost, holding cost, cycle service level and inventory turnover. We bridge the gap between theory and a real industrial problem and solve the formulated problem by using an interactive trade-off-free multiobjective optimization method called E-NAUTILUS. It is well suited for computationally expensive problems. We also propose a novel user interface for the method. As a proof of concept for the model and the method, we use real data from a manufacturing company with the manager as the decision maker. We consider two types of items and demonstrate how a decision maker can find a most preferred solution with the best balance among the conflicting objectives and gain valuable insight.
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ElsevierISSN Hae Julkaisufoorumista
0360-8352Asiasanat
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https://converis.jyu.fi/converis/portal/detail/Publication/159008945
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This research was partly funded by LPDP, the Indonesian Endowment Fund for Education (grant number S-5302/LPDP.4/2020) and the Academy of Finland (grant number 322221). 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.Lisenssi
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