Journal
INFORMS JOURNAL ON COMPUTING
Volume 12, Issue 3, Pages 237-255Publisher
INFORMS
DOI: 10.1287/ijoc.12.3.237.12636
Keywords
ant colony optimization; ant algorithms; metaheuristics; sequential ordering problem; swarm intelligence
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We present a new local optimizer called SOP-3-exchange for the sequential ordering problem that extends a local search for the traveling salesman problem to handle multiple constraints directly without increasing computational complexity. An algorithm that combines the SOP-3-exchange with an Ant Colony Optimization algorithm is described, and we present experimental evidence that the resulting algorithm is more effective than existing methods for the problem. The best-known results for many of a standard test set of 22 problems are improved using the SOP-a-exchange with our Ant Colony Optimization algorithm or in combination with the MPO/Al algorithm (Chen and Smith 1996).
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