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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...
Vehicle routing problem with time window (VRPTW) is a very important combinatorial optimization and nonlinear programming problem and it has important practical value in the field of transportation, distribution and logistics. Traditional intelligent optimization algorithms have the common defects of early convergence and easily falling into local optimal solution in solving VRPTW. An improved hybrid...
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...
Location-routing problem (LRP) is a combinational optimization problem in a logistics system. Most heuristic methods employed for LRP is dividing the problem into location assignment and vehicle routing with a two-phase method, but this method often does not lead to a satisfactory result for the information can not be compressed from one phase to the other efficiently. In this paper we are concerned...
Electronic commerce, as a new commercial mode, has its own particularity comparing with traditional commercial activities. In order to satisfy with the individual and various demand of customer under e-commerce, establish multi-depot vehicle routing problem with backhauls model. For MDVRPB is NP puzzle, get the optimization solution through adopting improved hybrid genetic algorithm, that is, use...
A modified genetic particle swarm optimization method (MGPSO) is employed to solve the capacitated vehicle routing problems (CVRP). MGPSO was derived from the standard particle swarm optimization (PSO) and incorporated with the genetic reproduction mechanisms, namely crossover and mutation. MGPSO employs an integer encoding and decoding representation, which is suitable for combinatorial optimization...
Considering the specialties of logistics distribution under electronic commerce, the traditional multi-depot vehicle scheduling model is modified in order to reduce the distribution cost; objective function is modified based on minimum expense. At the same time, in order to improve the distribution service quality and market competition, add maximum work time, many vehicle types, and maximum running...
Vehicle routing problems (VRP) arise in many real-life applications within transportation and logistics. This paper considers vehicle routing models in grain logistics (GLVRP) and its intelligent algorithm. The objective of GLVRP is to use a fleet of vehicles with specific capacity to serve a number of customers with fixed demand and time window constraints. In this paper, a novel real number encoding...
In the open vehicle routing problem (OVRP), a vehicle does not return to the depot after servicing the last customer on a route. The description of this variant of the standard vehicle routing problem appeared in the literature over 20 years ago, but it has still received little attention from researchers for a satisfactory solution. In this paper, a novel real number encoding method of particle swarm...
In this paper, a multi-depot vehicle routing problem with weight-related cost (MDVRPWRC) is discussed. It is an extension of the classical multi-depot vehicle routing problem (MDVRP) by treating the vehicle load, i.e. the total weight of freight in a vehicle, as a variable in the objective of model. The corresponding costs incurred by the vehicle load are considered in the objective function when...
The vehicle routing problem of logistics distribution is indispensability contents in logistics distribution optimization. In order to satisfy with the individual and various demand of customer, establish single and mixed fleet multi-depot vehicle routing problem with backhauls model. According to the characteristics of model, hybrid genetic algorithm is used to get the optimization solution. First...
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...
The Multi-Depot Vehicle Routing Problem with time-dependent and fuzzy travel time is very difficult to solve to optimality even for relatively small size instances. So few or no literatures have focused on the problem so far. But it is very close to real world and can make the schedule more availability and more flexible. So this paper focuses on modeling and solution of the problem. A model of MDVRPTW...
The intelligent optimization algorithm PBIL is applied to VRP. Faced to the concrete problem that the objective function is to minimize the cost and meet the time restriction. And the probability statistics for the road traffic status distributed in working hours is considered to decide the routing. The probability matrix of PBIL algorithm is modified with the quick velocity update strategy of particle...
Expected growth in use and implementation of wireless sensor networks (WSNs) in different environments and for different applications creates new security challenges. In WSNs, a malicious node may initiate incorrect path information, change the contents of data packets, and even hijack one or more genuine network nodes. As the network reliability completely depends on individual nodespsila presence...
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