Abstract
Linear ordering problem (LOP) is a well know NP-hard optimization problem attractive for its complexity, rich collection of testing data and variety of real world applications. It is also a popular benchmark for novel optimization and metaheuristic algorithms. In this paper, we compare the performance of genetic algorithms and differential evolution as efficient metaheuristic solvers of the LOP.KeywordsGenetic AlgorithmDifferential EvolutionProblem InstanceCombinatorial Optimization ProblemMetaheuristic AlgorithmThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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