论文信息 - A Swarm Optimizer Based on Multi-Criterion Decision Making, Part II: Case Study

A Swarm Optimizer Based on Multi-Criterion Decision Making, Part II: Case Study

Due to its generality, the traveling salesman problem (TSP) is widely used as a benchmark for testing the class of combinatorial optimization algorithms. In this paper, we test the performance of a novel swarm optimizer based on multi-criterion decision making. An over-all quality of 99% is reached by testing only a small fraction of all possible tours (8.2761e-048 of all possible tours in case of 43 cities).

A.I. El-Gallad | M.E. El-Hawary | M. El-Hawary | A. El-Gallad

[1] Alan J. Hoffman,et al. Aspects of the Traveling Salesman Problem , 1984, IBM J. Res. Dev..

[2] Gerhard Reinelt,et al. TSPLIB - A Traveling Salesman Problem Library , 1991, INFORMS J. Comput..

[3] Gilbert Laporte,et al. Routing problems: A bibliography , 1995, Ann. Oper. Res..

[4] Claus Rinner,et al. Personalized Multi-Criteria Decision Strategies in Location-Based Decision Support , 2004, Ann. GIS.

[5] Pedro Larrañaga,et al. Genetic Algorithms for the Travelling Salesman Problem: A Review of Representations and Operators , 1999, Artificial Intelligence Review.

[6] Rinner Claus,et al. Personalized Multi-Criteria Decision Strategies in Location-Based Decision Support , 2004 .

[7] A. Schrijver. On the History of Combinatorial Optimization (Till 1960) , 2005 .

[8] M. El-Hawary,et al. A Swarm Optimizer Based on Multi-Criterion Decision Making, part I: Theoretical investigation , 2006, 2006 Large Engineering Systems Conference on Power Engineering.