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Solving Dynamic Vehicle Routing: An Alternative Metaheuristic Approach

Amr BADR
Department of Computer Science, Faculty of Computers and Information
Cairo University

Abstract: An adapted Evolution strategy is proposed for solving the Dynamic (General) Vehicle Routing Problem (DVRP). Several Mutation and crossover operators are designed to deal with real-time demand information which is available only at the day of operation. A simulation was carried out in which intelligent planning of new online orders are dealt with. Several problems were generated to test the proposed algorithm. The problems were solved twice. First, they are solved off-line in which all orders are known prior to the day of operation. Second, they were solved in which orders are dynamic. The competitive ratio gave an average of 0.65.

Keywords: Dynamic Vehicle Routing; General Vehicle Routing; Adapted Evolution Strategy; Intelligent Real-time Planning.

Dr. Amr Badr is currently an Associate Professor of Computer Science at the Faculty of Computers and Information, Department of Computer Science, Cairo University. He received his BSc in Engineering with Honors. He received his MSc and PhD in Computer Science in 1995 and 1998 from Cairo University. He has published more than 50 Journal Research papers and is currently enrolled on the editorial boards of several international journals. His prime research interests are computational Intelligence, Bioinformatics and Medical imaging.

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CITE THIS PAPER AS:
Amr BADR,  Solving Dynamic Vehicle Routing: An Alternative Metaheuristic Approach, Studies in Informatics and Control, ISSN 1220-1766, vol. 18 (2), pp. 159-164, 2009.