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

Author

Ramkumar, A.S. ; Ponnambalam, S.G.

Author_Institution

Dept. of Production Eng., Amrita Sch. of Eng., AVVP

fYear

2006

fDate

7-9 June 2006

Firstpage

1

Lastpage

5

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

Keywords

combinatorial mathematics; computational complexity; facilities layout; minimisation; NP hard combinatorial optimization; assignment cost minimization; facility layout; machine layout; population based hybrid ant-colony system; quadratic assignment formulation metaheuristic; quadratic function; Algorithm design and analysis; Ant colony optimization; Benchmark testing; Cost function; Design optimization; Educational institutions; Genetic algorithms; Heuristic algorithms; Libraries; Production engineering; Quadratic Assignment Problem; ant colony optimization; guided local search; machine layout;

fLanguage

English

Publisher

ieee

Conference_Titel

Cybernetics and Intelligent Systems, 2006 IEEE Conference on

Conference_Location

Bangkok

Print_ISBN

1-4244-0023-6

Type

conf

DOI

10.1109/ICCIS.2006.252286

Filename

4017845