First Competitive Ant Colony Scheme for the CARP

作者: Philippe Lacomme , Christian Prins , Alain Tanguy

DOI: 10.1007/978-3-540-28646-2_48

关键词: Swarm intelligenceMetaheuristicHeuristicUpper and lower boundsAnt colonyComputer scienceGraph (abstract data type)PheromoneRate of convergenceGenetic algorithmLocal search (optimization)Artificial intelligenceMathematical optimization

摘要: The CARP consists on determining a set of vehicle trips with minimum total cost. Each trip starts and ends at the depot, each required edge site graph is serviced by one single trip, demand handled any does not exceed capacity Q. most efficient metaheuristics published so far are sophisticated taboo search method (CARPET) Hertz et al. [1] hybrid genetic algorithm proposed Lacomme [2]. In beginning, no collective memory used ants use only heuristic information. Pheromone deposition proportional to fitness that can be defined for minimization objectives as inverse solution quality or Local also applied increase convergence rate. process iterated until lower bound reached maximal number iterations carried out.

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