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A new genetic algorithm for vehicle routing problem.

Author(s)
Ziauddin Ursani School of Engineering & Information Technology, University of New South Wales, ADFA Campus, Northcott Drive, Canberra, ACT 2600, Australia
Ahsan Ahmad Ursani Institute of Information & Communication Technologies, Mehran University of Engineering & Technology, Jamshoro, Pakistan
Aftab Ahmed Memon Institute of Information & Communication Technologies, Mehran University of Engineering & Technology, Jamshoro, Pakistan
Abstract
The VRP (Vehicle Routing Problem) is a typical problem of combinatorial optimization. It is a product of two NP-Hard problems i.e., routing and assignment problem. In the past, a number of attempts have been made to solve this problem through various meta-heuristics including genetic algorithms. However, genetic algorithms have failed to compete with other paradigms in the area. Therefore there remains a great room for improvement for genetic algorithms as far as VRP is concerned. In this paper the authors proposed a new genetic algorithm augmented with a new evaluation procedure called self-imposed constraints. The algorithm is successfully tested on popular datasets, yielding encouraging results.
Publication Details
Page(s) 153-162
DOI DOI not available
Published Journal: Mehran University Research Journal of Engineering and Technology, Volume: 29, Issue: 1, Year: 2010

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