Production and Inventory Control of Assemble-to-Order Systems

Loading...
Publication Logo

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

Journal ISSN

Volume Title

Publisher

Springer Science and Business Media Deutschland GmbH

Open Access Color

Green Open Access

No

OpenAIRE Downloads

OpenAIRE Views

Publicly Funded

No
Impulse
Average
Influence
Average
Popularity
Average

Research Projects

Journal Issue

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

Fields of Science

Citation

WoS Q

Scopus Q

OpenCitations Logo
OpenCitations Citation Count
1

Source

International Symposium for Production Research ISPR2021

Volume

Issue

Start Page

End Page

PlumX Metrics
Citations

Scopus : 1

Captures

Mendeley Readers : 4

Google Scholar Logo
Google Scholar™
OpenAlex Logo
OpenAlex FWCI
0.6278

Sustainable Development Goals

SDG data is not available