Integrated Lot-sizing and Job Shop Scheduling Benefiting From Reconfigurable Machine Tools

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21730%2F22%3A00363448" target="_blank" >RIV/68407700:21730/22:00363448 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1016/j.ifacol.2022.09.567" target="_blank" >https://doi.org/10.1016/j.ifacol.2022.09.567</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.ifacol.2022.09.567" target="_blank" >10.1016/j.ifacol.2022.09.567</a>

Result language
angličtina
Original language name
Integrated Lot-sizing and Job Shop Scheduling Benefiting From Reconfigurable Machine Tools
Original language description
In recent years, the reconfigurable manufacturing system has received a great deal of attention as an effective manufacturing paradigm to tackle high diversity and volatility of demand. Its effective implementation requires responsive production planning to provide accurate capacity and functionality needed at any given time of the planning horizon. In the present work, an integrated lot-sizing and job shop scheduling problem as one of the most challenging problems in production planning is investigated considering reconfigurable machine tools. In this regard, a novel mathematical model is developed for simultaneous optimization of the lot-sizing, scheduling, and machine configuration to meet all demands with minimum operational costs, including setup, production, inventory holding, and machine reconfiguration. Three key performance indicators (KPIs) are considered to evaluate the system performance, including schedulability, optimality, and responsiveness. Finally, computational experiments are conducted affirming promising improvement in the KPIs by incorporating the machine reconfigurability in the integrated lot-sizing and job shop scheduling problem. Copyright (C) 2022 The Authors.
Czech name
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Czech description
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Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project
<a href="/en/project/LL1902" target="_blank" >LL1902: Powering SMT Solvers by Machine Learning</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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