An Effective PSO-Based Memetic Algorithm for TSP

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.

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