Production and Inventory Control of Assemble-to-Order Systems
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Date
2022
Authors
Nisa Saracalıoğlu
Yiğit Sonbahar
Güner Asrın Akdeniz
Meryem Ünsal
Yarkın Yiğit Yıldız
Salih Kaan Çakmakçı
Önder Bulut
Sinem Özkan
Ceylin Hökenek
Journal Title
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Volume Title
Publisher
Springer Science and Business Media Deutschland GmbH
Open Access Color
Green Open Access
No
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Publicly Funded
No
Abstract
In this study we consider an Assemble-to-Order (ATO) system with multiple components common machines and multiple customer classes. We first identify the research problems related to all the above-mentioned system features. Thereafter as the solution methodology we propose different policies for the described problems. We develop a simulation model of the system and benefit from Genetic Algorithm (GA) metaheuristic that finds near-optimal solutions for inventory control and rationing policies. The simulation model of a quite general ATO system that is integrated with a Genetic algorithm provides solutions for several real-life ATO practices. © 2022 Elsevier B.V. All rights reserved.
Description
Keywords
Assemble-to-order, Common Machine Scheduling, Production-inventory Control Policy, Rationing Policy, Simulation Optimization, Inventory Control, Assemble To Order, Common Machine Scheduling, Inventory Control Policies, Machine Scheduling, Ordering System, Production-inventory Control, Production-inventory Control Policy, Rationing Policy, Simulation Model, Simulation Optimization, Genetic Algorithms, Inventory control, Assemble to order, Common machine scheduling, Inventory control policies, Machine scheduling, Ordering system, Production-inventory control, Production-inventory control policy, Rationing policy, Simulation model, Simulation optimization, Genetic algorithms
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Scopus Q

OpenCitations Citation Count
1
Source
International Symposium for Production Research ISPR2021
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Scopus : 1
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