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Evolving TSP Heuristics using Multi Expression Programming

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (2004) 3037 670-673
DOI: 10.1007/978-3-540-24687-9_99
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Abstract

Multi Expression Programming (MEP) is used for evolving a Traveling Salesman Problem (TSP) heuristic for graphs satisfying triangle inequality. Evolved MEP heuristic is compared with Nearest Neighbor Heuristic (NN) and Minimum Spanning Tree Heuristic (MST) on some difficult problems in TSPLIB. The results emphasizes that evolved MEP heuristic is better than the compared algorithm for the considered test problems. © Springer-Verlag Berlin Heidelberg 2004.

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Oltean, M., & Dumitrescu, D. (2004). Evolving TSP Heuristics using Multi Expression Programming. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3037, 670–673. https://doi.org/10.1007/978-3-540-24687-9_99

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