A comparison of two methods for solving 0–1 integer programs using a general purpose simulated annealing algorithm |
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| Authors: | David Abramson Henry Dang Mohan Krishnamoorthy |
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| Institution: | (1) School of Computing and Information Technology, Griffith University, Kessels Road, 4111 Nathan, Qld, Australia;(2) Department of Computer Systems Engineering, Royal Melbourne Institute of Technology, P.O.Box 2476V, 3001, Vic, Australia;(3) Division of Mathematics and Statistics, CSIRO, Rosebank MDC, Private Bag 10, 3168 Clayton, Vic, Australia |
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| Abstract: | 0–1 problems are often difficult to solve. Although special purpose algorithms (exact as well as heuristic) exist for solving
particular problem classes or problem instances, there are few general purpose algorithms for solving practical-sized instances
of 0–1 problems. This paper deals with a general purpose heuristic algorithm for 0–1 problems. In this paper, we compare two
methods based on simulated annealing for solving general 0–1 integer programming problems. The two methods differe in the
scheme used for neighbourhood transitions in the simulated annealing framework. We compare the performance of the two methods
on the set partitioning problem. |
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