A Path Relinking Approach for the Multi-Resource Generalized Quadratic Assignment Problem
- 597 Downloads
We consider the multi-resource generalized quadratic assignment problem (MR-GQAP), which has many applications in various fields such as production scheduling, and constitutes a natural generalization of the generalized quadratic assignment problem (GQAP) and the multi-resource generalized assignment problem (MRGAP). We propose a new algorithm PR-CS for this problem that proves highly effective. PR-CS features a path relinking approach, which is a mechanism for generating new solutions by combining two or more reference solutions. It also features an ejection chain approach, which is embedded in a neighborhood construction to create more complex and powerful moves. Computational comparisons on benchmark instances show that PR-CS is more effective than existing algorithms for GQAP, and is competitive with existing methods for MRGAP, demonstrating the power of PR-CS for handling these special instances of MR-GQAP without incorporating special tailoring to exploit these instances.
KeywordsLocal Search Assignment Problem Constraint Satisfaction Problem Benchmark Instance Quadratic Cost
Unable to display preview. Download preview PDF.
- 5.Glover, F.: Ejection chains, reference structures and alternating path methods for traveling salesman problems, Research Report, University of Colorado, Boulder, CO. Discrete Applied Mathematics 65, 223–253 (1996)Google Scholar
- 6.Ibaraki, T., Ohashi, T., Mine, H.: A heuristic algorithm for mixed-integer programming problems. Mathematical Programming Study 2, 115–136 (1974)Google Scholar
- 7.Laguna, M., Martí, R.: Scatter Search: Methodology and Implementations in C. Kluwer Academic Publishers, Boston (2003)Google Scholar
- 8.Lee, C., Ma, Z.: The generalized quadratic assignment problem, Technical Report. Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, Ontario, Canada (2003)Google Scholar
- 11.Voss, S.: Heuristics for nonlinear assignment problems. In: Pardalos, P.M., Pitsoulis, L.S. (eds.) Nonlinear Assignment Problems, pp. 175–215. Kluwer Academic Publishers, Dordrecht (2000)Google Scholar