A self-organizing neural network approach for the single AGV routing problem

In this research, a special form of Automated Guided Vehicle (AGV) routing problem is investigated. The objective is to find the shortest tour for a single, free-ranging AGV that has to carry out multiple pick and deliver (P&D) requests. This problem is an incidence of the asymmetric traveling s...

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Bibliographic Details
Published in:European journal of operational research 2000-02, Vol.121 (1), p.124-137
Main Authors: Soylu, Mustafa, Özdemirel, Nur E., Kayaligil, Sinan
Format: Article
Language:English
Subjects:
AGV routing
AGVS
Asymmetric traveling salesman problem
Neural networks
Operations research
Self-organizing maps
Studies
Traveling salesman problem
Variance analysis
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Summary:In this research, a special form of Automated Guided Vehicle (AGV) routing problem is investigated. The objective is to find the shortest tour for a single, free-ranging AGV that has to carry out multiple pick and deliver (P&D) requests. This problem is an incidence of the asymmetric traveling salesman problem which is known to be NP-complete. An artificial neural network algorithm based on Kohonen's self-organizing feature maps is developed to solve the problem, and several improvements on the basic features of self-organizing maps are proposed. Performance of the algorithm is tested under various parameter settings for different P&D request patterns and problem sizes, and compared with the optimal solution and the nearest neighbor rule. Promising results are obtained in terms of solution quality and computation time.
ISSN:0377-2217
1872-6860
DOI:10.1016/S0377-2217(99)00032-6