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Evolving Combinatorial Problem Instances That Are Difficult to Solve
2006
Evolutionary Computation
In this paper we demonstrate how evolutionary computation can be used to acquire difficult to solve combinatorial problem instances, thereby stress-testing the corresponding algorithms used to solve these instances. The technique is applied in three important domains of combinatorial optimisation, binary constraint satisfaction, Boolean satisfiability, and the travelling salesman problem. Problem instances acquired through this technique are more difficult than ones found in popular benchmarks.
doi:10.1162/evco.2006.14.4.433
pmid:17109606
fatcat:togz2qqffrcptjkiwwbke42vl4