Cognitive Hybrid PSO/SA Combinatorial Optimization

Abstract

This paper presents a population based simulated annealing algorithm to improve modelling of cognitive processes. Particle Swarm Optimization (PSO) is embedded within the basic Simulated Annealing (SA) algorithm to allow for multiple concurrent candidate solutions through the use of a population-driven social coefficient updating the other population members. A modified ramping strategy which balances inertial, personal and swarm coefficients is introduced. The hybrid PSO/SA algorithm was tested on the travelling salesperson problem (TSP), and was shown to outperform the individual algorithms by improving their limitations in exploration and exploitation.