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Integrated locating in-house logistics areas and transport vehicles selection problem in assembly lines
University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. Faculty of Industrial & Systems Engineering, Tarbiat Modares University, Tehran, Iran. (Production and Automation Engineering)ORCID iD: 0000-0001-6280-1848
Faculty of Management and Economics, Tarbiat Modares University, Tehran, Iran / School of Management, Swansea University, UK.
University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. (Production and Automation Engineering)ORCID iD: 0000-0001-5530-3517
University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. (Production and Automation Engineering)ORCID iD: 0000-0003-0111-1776
2019 (English)In: International Journal of Production Research, ISSN 0020-7543, E-ISSN 1366-588XArticle in journal (Refereed) Epub ahead of print
Abstract [en]

Decentralised in-house logistics areas, known as supermarkets, are widely used in the manufacturing industry for parts feeding to assembly lines. In contrary to the literature and inspired by observation in a real case, this study relaxes the assumption of using identical transport vehicles when deciding on the supermarkets’ location by considering the availability of different vehicles. In this regard, this study deals with the integrated supermarket location and transport vehicles selection problems (SLTVSP). A mixed-integer programming (MIP) model of the problem is developed. Due to the complexity of the problem, a hybrid genetic algorithm (GA) with variable neighborhood search (GA-VNS) is also proposed to address large-sized problems. The performance of GA-VNS is compared against the MIP, the basic GA, and simulated annealing (SA) algorithm. The computational results from the real case and a set of generated test problems show that GA-VNS provides a very good approximation of the MIP solutions at a much shorter computational time while outperforming the other compared algorithms. The analysis of the results reveals that it is beneficial to apply different transport vehicles rather than identical vehicles for SLTVSP.

Place, publisher, year, edition, pages
Taylor & Francis, 2019.
Keywords [en]
In-house logistics, supermarket location, parts feeding, transport vehicles, mixed-integer programming, genetic algorithm
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
Production and Automation Engineering
Identifiers
URN: urn:nbn:se:his:diva-18018DOI: 10.1080/00207543.2019.1701207ISI: 000503313800001Scopus ID: 2-s2.0-85076905476OAI: oai:DiVA.org:his-18018DiVA, id: diva2:1380021
Available from: 2019-12-18 Created: 2019-12-18 Last updated: 2020-02-19Bibliographically approved

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Nourmohammadi, AmirFathi, MasoodNg, Amos H. C.

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