Hybrid Ant colony System for solving Quadratic Assignment Formulation of Machine Layout Problems

Abstract

The quadratic assignment problems (QAPs) are the problem of assigning 'n' facilities to 'n' locations so that the assignment cost is minimized, where the cost is defined by a quadratic function. In this paper we investigate and present the application of population based hybrid ant-colony system (PHAS) metaheuristic for solving machine (facility) layout problems formulated as quadratic assignment problem, a well-known NP hard combinatorial optimization problem. Ant-colony system is a model for designing metaheuristic algorithms for combinatorial optimization problems. The PHAS ant system algorithm incorporates population-based ants in its initial phase instead of small number of ants and probability based pheromone trail modification. We tested our algorithm on the benchmark instances of QAPLIB, a well-known library of QAP instances and the obtained solution quality is compared with solution obtained with standard guided local search algorithm for the same QAP