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.
...
Julkaisija
ElsevierISSN Hae Julkaisufoorumista
0360-8352Asiasanat
Julkaisu tutkimustietojärjestelmässä
https://converis.jyu.fi/converis/portal/detail/Publication/159008945
Metadata
Näytä kaikki kuvailutiedotKokoelmat
Rahoittaja(t)
Suomen AkatemiaRahoitusohjelmat(t)
Akatemiahanke, SALisätietoja rahoituksesta
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
Samankaltainen aineisto
Näytetään aineistoja, joilla on samankaltainen nimeke tai asiasanat.
-
Flexible data driven inventory management with interactive multiobjective lot size optimization
Heikkinen, Risto; Sipilä, Juha; Ojalehto, Vesa; Miettinen, Kaisa (Inderscience Publishers, 2023)We study data-driven decision support and formalise a path from data to decision making. We focus on lot sizing in inventory management with stochastic demand and propose an interactive multi-objective optimisation approach. ... -
Interactive Multiobjective Optimization in Lot Sizing with Safety Stock and Safety Lead Time
Kania, Adhe; Sipilä, Juha; Afsar, Bekir; Miettinen, Kaisa (Springer, 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 ... -
A Performance Indicator for Interactive Evolutionary Multiobjective Optimization Methods
Aghaei Pour, Pouya; Bandaru, Sunith; Afsar, Bekir; Emmerich, Michael; Miettinen, Kaisa (IEEE, 2024)In recent years, interactive evolutionary multiobjective optimization methods have been getting more and more attention. In these methods, a decision maker, who is a domain expert, is iteratively involved in the solution ... -
An Approach to the Automatic Comparison of Reference Point-Based Interactive Methods for Multiobjective Optimization
Podkopaev, Dmitry; Miettinen, Kaisa; Ojalehto, Vesa (Institute of Electrical and Electronics Engineers (IEEE), 2021)Solving multiobjective optimization problems means finding the best balance among multiple conflicting objectives. This needs preference information from a decision maker who is a domain expert. In interactive methods, the ... -
Desirable properties of performance indicators for assessing interactive evolutionary multiobjective optimization methods
Aghaei Pour, Pouya; Bandaru, Sunith; Afsar, Bekir; Miettinen, Kaisa (ACM, 2022)Interactive methods support decision makers in finding the most preferred solution in multiobjective optimization problems. They iteratively incorporate the decision maker's preference information to find the best balance ...
Ellei toisin mainittu, julkisesti saatavilla olevia JYX-metatietoja (poislukien tiivistelmät) saa vapaasti uudelleenkäyttää CC0-lisenssillä.