On the analysis of the (1+ 1) evolutionary algorithm
Theoretical Computer Science
Combining convergence and diversity in evolutionary multiobjective optimization
Evolutionary Computation
Ant Colony Optimization
Multicriteria Optimization
Crossover can provably be useful in evolutionary computation
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Analysis of a simple evolutionary algorithm for the multiobjective shortest path problem
Proceedings of the tenth ACM SIGEVO workshop on Foundations of genetic algorithms
Improved analysis methods for crossover-based algorithms
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
IEEE Transactions on Evolutionary Computation
How crossover helps in pseudo-boolean optimization
Proceedings of the 13th annual conference on Genetic and evolutionary computation
An analysis on recombination in multi-objective evolutionary optimization
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Evolutionary algorithms and dynamic programming
Theoretical Computer Science
Running time analysis of Ant Colony Optimization for shortest path problems
Journal of Discrete Algorithms
Crossover speeds up building-block assembly
Proceedings of the 14th annual conference on Genetic and evolutionary computation
Impact of different recombination methods in a mutation-specific MOEA for a biochemical application
EvoBIO'13 Proceedings of the 11th European conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics
An analysis on recombination in multi-objective evolutionary optimization
Artificial Intelligence
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Understanding the impact of crossover in evolutionary algorithms is one of the major challenges in the theoretical analysis of these stochastic search algorithms. Recently, it has been shown that crossover provably helps to speed up evolutionary algorithms for the classical allpairs-shortest path (APSP) problem. In this paper, we extend this approach to the NP-hard multi-criteria APSP problem. Based on rigorous runtime analyses, we point out that crossover leads to better worst case bounds than previous known results. This is the first time that rigorous runtime analyses have shown the usefulness of crossover for an NP-hard multi-criteria optimization problem.