In this work the development and implementation of a Decision Support System is described. It will assist in the route calculation process and in optimizing the filling of the trucks that have to transport a considerably number of vehicles from near of 8 origins to more than 3,000 possible destinations spread over Spain and Portugal, and some in France, Germany, etc. The problem can be classifi...

Vehicle-routing problems (VRP), which can be considered a generalization of TSP, have been studied in depth. Many variants of the problem exist, most of them trying to find a set of routes with the shortest distance or time possible for a fleet of vehicles. This paper combines two important variants, the stochastic time-dependent VRP and the multi-objective VRP. A genetic algorithm for solving ...

Vehicle Routing Problem (VRP) is a key element of many transportation systems which involve routing of fleet of vehicles from a depot to a set of customers node. It is required that these vehicles return to the depot after serving customers’ demand. This paper investigates a relaxed version of VRP, in which the number of visits to the customer is not restricted to be at most one. The relaxed ve...

The vehicle routing problem (VRP) is a difficult and well-studied combinatorial optimization problem. We develop a parallel algorithm for the VRP that combines a heuristic local search improvement procedure with integer programming. We run our parallel algorithm with as many as 129 processors and are able to quickly find high-quality solutions to standard benchmark problems. We assess the impac...

The Vehicle Routing Problem (VRP) is a highly investigated logistics problem. VRP can model in-plant and out-plant material handling or whole supply chain. first article was published in 1959 by Dantzig Ramser, many varieties of have appeared since then. Transport systems are becoming more customized these days, so it necessary to develop general system that covers transport tasks. Based on the...

HIV-1 genetic diversity among circulating strains presents a major challenge for HIV-1 vaccine development, particularly for developing countries where less sequence information is available. To identify representative viruses for inclusion in candidate vaccines targeted for South Africa, we applied an efficient sequence survey strategy to samples from recently and chronically infected persons ...

The vehicle routing problem (VRP) is a difficult and well-studied combinatorial optimization problem. Real-world instances of the VRP can contain hundreds and even thousands of customer locations and can involve many complicating constraints, necessitating the use of heuristic methods. We present a software library of local search heuristics that allow one to quickly generate solutions to VRP i...

We present an end-to-end framework for solving Vehicle Routing Problem (VRP) using deep reinforcement learning. In this approach, we train a single model that finds near-optimal solutions for problem instances sampled from a given distribution, only by observing the reward signals and following feasibility rules. Our model represents a parameterized stochastic policy, and by applying a policy g...

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The vehicle routing problem (VRP), a well-known combinatorial optimization problem, holds a central place in logistics management. Many meta-heuristic approaches like Simulated Annealing (SA), Genetic Algorithms (GA), Tabu Search (TS), and Ant Colony Optimization (ACO) have been proposed to solve VRP. Ant Algorithm is a distributed meta-heuristic approach that has been applied to various combin...