A new strategy to improve the search performance of Max-Min Ant Aystem Algorithm when solving the Quadratic Assignment Problems

Abstract

The use of Ant Colony Optimizations (ACOs) to solve Combinatorial Optimization (CO) problems has increase rapidly. Particularly, researchers have started to seek for improvement in ACOs through various innovative methodologies. Among others is the use of innovative pheromone manipulation strategy, the modification of ACOs framework, and hybridization of ACOs with other metaheuristic algorithms. This paper presents a new pheromone manipulation strategy called the Minimum Pheromone Threshold Strategy (MPTS), which is able to enhance the search performance of the Max-Min Ant System (MMAS) algorithm (a variant of ACO).