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The vehicle routing problem is proved to be a kind of NP problem. Immune genetic algorithm is proposed based on genetic algorithm and the use of the biological and immune system in this paper. A kind of group diversity maintaining strategy based on the density of individual is constructed. An immune operator and a immune memory library are applied to the algorithm. The experimental results of a VRP...
Vehicle Routing Problem (VRP) is an important class of scheduling optimization problems in the supply chain management. Vehicle Routing Problem with Time Windows (VRPTW) is an extension of VRP and involves the setoff of a fleet of vehicles from a depot to serve a number of customers at different geographic locations for within specific time windows before returning to the depot eventually. This study...
To improve the performance of particle swarm optimization and differential evolution, the diploid differential evolution particle swarm optimization was presented according to the genetics rules. The algorithm was applied into the Open Vehicle Routing Problem. In the algorithm, dominant character and recessive character were included in every individual. Particle swarm optimization was implemented...
In this paper, the vehicle routing problem with time windows (VRPTW) was considered, and a mixed integer programming mathematic model of VRPTW was proposed in detail. Meantime, an improved genetic algorithm (IGA) was proposed to overcome the shortcomings of premature convergence and slow convergence of conventional genetic algorithm (GA). The novel crossover-operator, swapping operator and inversion...
A new method for solving vehicle routing problems with time-window (VRPTW) based on bee evolutionary genetic algorithm (BEGA) is proposed. By adding a delivery vehicle fixed cost to the fitness function, the contradictory between the number of vehicles and driving distance at the same time is solved effectivity. Self-adaptive crossover operator is adopted to increase the accuracy of optimization and...
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...
VRP is the problem of NP of a kind of typical case. This paper is put forward an improved immune clonal selection algorithm (ICSA) through introducing cloning operator to solve the VRP problem. The algorithm through the introduction of clonal proliferation, super mutation operators and clonal selection operators, improves the global convergence speed, and can effectively avoid prematurity. Through...
In order to satisfy with the individual and various demand of customer, establish vehicle scheduling with backhauls model. According to the characteristics of model, hybrid genetic heuristic algorithm is used to get the optimization solution. First of all, use natural number coding so as to simplify the problem; retain the best selection so as to guard the diversity of group. Improved ordinal crossover...
This paper based on the manipulation of full vehicle logistic network and integrated inventory, in order to optimize automobile logistics network and reduce costs, the integrated optimization model was presented, which provided an integrated view of transportation economies-of-scale, inventory and facility costs as well as service quality, and at the same time a complicated multi-customer network...
The standard simulated algorithm has been applied into vehicle routing problem, and it has the common defects of slow convergence and easily being trapped into local minima. In this paper, a new stochastic approach called the simulated annealing genetic algorithm is proposed to solve stochastic vehicle routing problems and the solution is then compared with that from simulated algorithm. Results from...
To resolve vehicle routing problem in logistic field, genetic arithmetic and ant colony arithmetic are often employed, and each runs with merit and defect. In the paper, two algorithm thinking are integrated based on each trait. Firstly a rapid and excellent solution arises in anterior genetic operation, and initial information elements derive from the solution, and then ant colony arithmetic starts...
Particle Swarm Optimizer (PSO) has several shortages when it is used for searching the best route of combinatorial optimization problems including vehicle routing and scheduling problems (VRSP), such as the premature convergence and easily limited to local optimal solution. The article proposed an improved PSO to overcome these shortcomings and improve its performance. The proposed algorithm integrates...
The logistic distribution has the characteristic of dispersive customer positions, little batches and many repeated routes under common distribution. Therefore, according to the particularity of logistic distribution, the improved cluster first/route second algorithm is adopted to get solutions. Namely, the customer group can be divided into several regions using k-means algorithm in first phase....
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