Algorithms for the vehicle routing problems with time deadlines
American Journal of Mathematical and Management Sciences - Special issue: vehicle routing 2000: advances in time windows, optimality, fast bounds, & multi-depot routing
Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic algorithms + data structures = evolution programs (3rd ed.)
Uniform Crossover in Genetic Algorithms
Proceedings of the 3rd International Conference on Genetic Algorithms
Particle Swarm Optimization for the Vehicle Routing Problem with Stochastic Demands
Applied Soft Computing
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This paper deals with a real-life vehicle routing problem concerning the distribution of products to customers. A non-homogenous fleet of trucks with limited capacity and allowed travel time is available to satisfy the stochastic multiple product demand of a set of different types of customers with earliest and latest time for servicing. The objective is to minimize distribution costs while maximizing customer satisfaction and respecting the constraints concerning the vehicle capacity, the time windows for customer service and the driver working hours per day. A model describing all these requirements has been developed as well as a genetic algorithm to solve the problem. High Performance Computing has been used to allow the pursuit for a near-optimal solution in a sensible amount of time, as the parallel chromosome fitness evaluation counterbalances the increased size and complexity of the problem.