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Vehicle routing is a critical factor in reducing transportation costs. Finding optimal vehicle routes offers great potential to efficiently manage fleets, reduce costs and improve service quality. An effective scheme to manage fleets and determine vehicle routes for delivering goods is important for carriers to survive. In the existing literature, a variety of vehicle routing problems (VRP) have been...
Vehicle Routing Problem (VRP) is a well known NP-hard optimization problem with a number of real world applications and a variety of different versions. Due to its complexity, large instances of VRP are hard to solve using exact methods. Instead, various heuristic and meta-heuristic algorithms were used to find feasible VRP solutions. This work proposes a Differential Evolution for VRP that simultaneously...
The artificial bee colony algorithm (ABC) with three loading heuristics for the two-dimensional loading capacitated vehicle routing problem (2L-CVRP) is presented in the paper. The 2L-CVRP is a combination of two well-known NP-hard problems, the capacitated vehicle routing problem, and the two-dimensional bin packing problem. It is very difficult to get a good performance solution in practice for...
The vehicle routing problem is a class of problems that frequently occurs in the field of transportation logistics. In this work, we tackle very-large scale problem instances with time windows. Among other techniques, metaheuristics are frequently used to solve large-scale instances close to optimality. We present an island-model genetic algorithm variant and apply several techniques such as offspring...
Based on the traditional theory and algorithms of vehicle routing problem, the multi-objective VRPSDP mathematical model is established in considering the minimum of the number of vehicles and the transportation costs. The genetic algorithm is used as the solving algorithm of the model in this paper, in order to ensure the effectiveness of the chromosomes in the iterative process, the chromosome encoding...
This study primarily focuses on solving the vehicle routing problem with soft time windows (VRPSTW) by applying an improved double-population genetic algorithm (DPGA). The traditional single-population genetic algorithm (SPGA) in solving vehicle routing problem usually traps in local optimum or consumes considerable time. In this paper two different initialization methods - random initialization method...
Vehicle routing problem (VRP) is an important and well-known combinatorial optimization problem encountered in many transport logistics and distribution systems. The VRP has several variants depending on tasks performed and on some restrictions, such as time windows, multiple vehicles, backhauls, simultaneous delivery and pick-up, etc. In this paper, we consider vehicle routing problem with simultaneous...
Many distribution companies must deliver and pick up goods to satisfy customers. This problem is called the Vehicle Routing Problem with Mixed linehauls and Backhauls (VRPMB) which considers that some goods must be delivered from a depot to linehaul customers, while others must be picked up at backhaul customers to be brought to the depot. This paper studies an enriched version called Heterogeneous...
In order to solve the problem of slow convergence speed of adaptive genetic algorithm (AGA) in the early stage of evolution, an improved adaptive genetic algorithm (IAGA) was presented. With the introduction of an indicator evaluating the degree of population diversity, the new algorithm can adaptively adjust the probabilities of crossover. Furthermore, the IAGA was applied to vehicle routing problem...
The Vehicle Routing Problem has been a popular research topic in logistics (Physical distribution) which is of much practical value. This thesis puts forward the method of solving vehicle routing problem by the immune algorithm. In the solution procedure, this thesis creates a new encoded model which can increase the operational efficiency of the algorithm presented by decreasing the encoding length...
This paper study on the MDVRP with vehicle sharing, the vehicles can come to any depots. And we present an improved genetic algorithm with chromosome representing the clients. A typical result and the analysis of experiment indicate the validity of the method to solve the MDVRP.
To overcome the common defects of early convergence in the existing genetic algorithm, an improved genetic algorithm with new crossover operator and new crossover strategy was presented for the solution to the vehicle routing problem with soft time window (VRPTW). Experiments show that the improved genetic algorithm can dramatically reduce the number of same or similar chromosomes, and increase the...
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