| Document Date: 2013-06-23 23:44:47
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City Bruxelles / Brussels / / Company Intel / / Country Belgium / / / Facility IRIDIA laboratory / / IndustryTerm variation operator / upd solutions / higher quality solutions / sense to have different solution / iteration-best solutions / upd best solutions / software framework / optimization algorithms / mACO2 algorithms / feasible solution / partial solution / automatic algorithm / local search / performing algorithms / local search algorithms / stochastic local search / candidate solution / multi-objective evolutionary algorithm / e.g. local search / above algorithm / candidate solutions / multiobjective combinatorial optimization algorithms / multiobjective algorithms / automatic configuration tool / feasible solutions / secondbest solution / / OperatingSystem Linux / CentOS / / Person Luis Paquete / / / Position Colonel / The Bi-objective Traveling Salesman / representative / salesman / / ProgrammingLanguage TSP / / PublishedMedium IEEE Transactions on Evolutionary Computation / / Technology MOACO algorithms / existing MOACO algorithms / multi-objective evolutionary algorithm / Main algorithm / above algorithm / singleobjective ACO algorithms / underlying ACO algorithm / ACO algorithms / ACO algorithm / ten MOACO algorithms / MOACO algorithm / multiobjective combinatorial optimization algorithms / Linux / particular underlying ACO algorithm / optimization algorithms / VPN / local search algorithms / http / mACO2 algorithms / multi-colony BicriterionAnt algorithm / multi-objective algorithms / 1 1 1 2 1 2 2 1 1 Algorithm / one specific MOACO algorithm / high performing algorithms / pheromones / /
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FINAL DRAFT PUBLISHED IN IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION 1 The Automatic Design of Multi-Objective Ant Colony Optimization Algorithms