A method named strong gene schema combination algorithm(GSCA) is proposed based on evolutionary
algorithm, which gives the definitions of strong gene schema, continuous schema and symmetrical schema. Then the strong
gene schemas are extracted by using saving algorithm. Operators of selection, mutation and schema recombination are
designed. At the same time, the mathematical model of vehicle routing problem is established with the goal of transportation
cost and the restraints of customer requirements, truckload ability and time window(VRPTW). The effect of GSCA compared
with improved genetic algorithm(IGA), improved differential evolution algorithm(IDEA) and saving algorithm(SA) for
capturing the global optimum is tested on the VRPTW model in Matlab. The results show that the application of strong
gene schema and the operator of schema recombination reduce the number of searches greatly within the solution space and
enhance the convergence capability and the precision of the solution, and its performance is demonstrated better than the
compared three algorithms.