An effective PSO-based memetic algorithm for TSP. (English) Zbl 1202.90264
Huang, De-Shuang (ed.) et al., Intelligent computing in signal processing and pattern recognition. International conference on intelligent computing, ICIC 2006, Kunming, China, August 16–19, 2006. Berlin: Springer (ISBN 3-540-37257-1/pbk). Lecture Notes in Control and Information Sciences 345, 1151-1156 (2006).
Summary: This paper proposes an effective Particle Swarm Optimization (PSO) based Memetic Algorithm (MA) for Traveling Salesman Problem (TSP) which is a typical NP-hard combinatorial optimization problem with strong engineering background. In the proposed PSO-based MA (PSOMA), a novel encoding scheme is developed, and an effective local search based on Simulated Annealing (SA) with adaptive meta-Lamarckian learning strategy is proposed and incorporated into PSO. Simulation results based on well-known benchmarks and comparisons with some existing algorithms demonstrate the effectiveness of the proposed hybrid algorithm for TSP.
For the entire collection see [Zbl 1103.94002].
For the entire collection see [Zbl 1103.94002].
MSC:
| 90C35 | Programming involving graphs or networks |
| 90C59 | Approximation methods and heuristics in mathematical programming |
| 68T05 | Learning and adaptive systems in artificial intelligence |
