Performance Evaluation of Ant Colony Systems for the Single-Depot Multiple Traveling Salesman Problem

• Published in: Hybrid Artificial Intelligent Systems pp. 257 - 268
• Main Authors: Necula, Raluca, Breaban, Mihaela, Raschip, Madalina
• Format: Book Chapter
• Language: English
• Published: Cham Springer International Publishing
• Series: Lecture Notes in Computer Science
• Subjects: Ant colony optimization; Clustering; Multiple-TSP
• ISBN: 331919643X; 9783319196435
• DOI: 10.1007/978-3-319-19644-2_22

Derived from the well-known Traveling Salesman problem (TSP), the multiple-Traveling Salesman problem (multiple-TSP) with single depot is a straightforward generalization: several salesmen located in a given city (the depot) need to visit a set of interconnected cities, such that each city is visited exactly once (by a single salesman) while the total cost of their tours is minimized. Designed for shortest path problems and with proven efficiency for TSP, Ant Colony Systems (ACS) are a natural choice for multiple-TSP as well. Although several variations of ant algorithms for multiple-TSP are reported in the literature, there is no clear evidence on their comparative performance. The contribution of this paper is twofold: it provides a benchmark for single-depot-multiple-TSP with reported optima and performs a thorough experimental evaluation of several variations of the ACS on this problem.