Abstract
The transportation service for the cluster of small and medium enterprises (SMEs) is different with traditional vehicle routing problems. In the cluster of SMEs, parts of enterprises are pickup and delivery spots simultaneously. But some enterprises are partly pickup and delivery simultaneously. Traditional mathematics models and algorithms are not suitable to solve the vehicle routing problem partly simultaneous pickup and delivery (VRPPSD). In this paper, a mathematics operational model is proposed to analyze the transportation service of the cluster companies. A hybrid algorithm which is composed by tabu search, genetic algorithm and local search is used to optimize the operational model. The crossover and mutation contained by genetic algorithm is used to generate neighborhood solutions for tabu search. The data of a cluster of SMEs, investigating from Changzhou city, China, are employed to show the validity of our model. The results indicate that our model and hybrid algorithm is effective to solve VRPPSD. In this paper, the satisfied solutions of VRPPSD are found by hybrid algorithm. At the same time, the results also show that carriers with optimal routs can service customers with more profits (increasing 5.6%). The potential saving of transport cost will increase profits of carriers in SMEs.
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