Evolutionary programming algorithm for constrained optimal planning problems

An evolutionary programming algorithm for constrained nonlinear programming problems was proposed. The organization of the most pivotal mutation sub-operator in this algorithm was based on behavioral architecture. Several mutation sub-operators were designed for the practical needs. A weighted method was used to decide the whole mutation direction. Using niche technology and the best-be held strategy to assure the diversity and the global optimum of the population, this algorithm can gain the optimal solution quickly. At the same time, the problem of path planning of the mobile robot can be classified into general nonlinear programming problems based on the district-partition modeling method. The application of the path planning of the mobile robot in dynamic environment showed that the algorithm was feasible and efficient.