Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/195646
Authors: 
Pourrahimian, Parinaz
Year of Publication: 
2018
Citation: 
[Journal:] Journal of Industrial Engineering International [ISSN:] 2251-712X [Volume:] 14 [Year:] 2018 [Issue:] 4 [Pages:] 845-855
Abstract: 
Automated Guided Vehicle System (AGVS) provides the flexibility and automation demanded by Flexible Manufacturing System (FMS). However, with the growing concern on responsible management of resource use, it is crucial to manage these vehicles in an efficient way in order reduces travel time and controls conflicts and congestions. This paper presents the development process of a new Memetic Algorithm (MA) for optimizing partitioning problem of tandem AGVS. MAs employ a Genetic Algorithm (GA), as a global search, and apply a local search to bring the solutions to a local optimum point. A new Tabu Search (TS) has been developed and combined with a GA to refine the newly generated individuals by GA. The aim of the proposed algorithm is to minimize the maximum workload of the system. After all, the performance of the proposed algorithm is evaluated using Matlab. This study also compared the objective function of the proposed MA with GA. The results showed that the TS, as a local search, significantly improves the objective function of the GA for different system sizes with large and small numbers of zone by 1.26 in average.
Subjects: 
AGVS
Tandem configuration
Tabu search
Memetic algorithm
Genetic algorithm
Persistent Identifier of the first edition: 
Creative Commons License: 
https://creativecommons.org/licenses/by/4.0/
Document Type: 
Article

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