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The objective function of the vehicle routing problem with time windows (VRPTW) considered here is to achieve the minimization of total cost in a single distribution, which includes the travel costs and the penalty coefficient of time, under the constraints of time limits, volume and capacity. There are two main lines of development in relation to the exact algorithms for the VRPTW. One is concerned with the general decomposition approach and the solution to certain dual problems associated with the VRPTW. Another, more recent direction is concerned with the analysis of the polyhedral structure of the VRPTW. The algorithm to solve this model is a new stochastic approach called Genetic Simulated Annealing Algorithm (GSAA), which added both memory function and annealing operation to the algorithm. The result was compared to the former which operated by genetic algorithm, and showed that the approach to solve the VRPTW is very competitive

Soft Time Windows Associated Vehicles Routing Problems of Logistics Distribution Center Using Genetic Simulated Annealing Algorithm