关键词: 车辆路径规划, 改进混合智能算法, 模糊机会约束规划, 物料配送

Abstract: Material distribution of mixed-model assembly is a complex system for supporting assembly line operation. Accurate distribution in time can ensure continuous production and greatly improve production efficiency. However, there often exist uncertain factors, such as work station demand for goods, appointed goods arrival time, and vehicle transportation time, so the traditional route programming model cannot truly reflect the field situation and on the contrary will cause low productivity. The uncertain factors are taken into consideration, the chance constraint programming model under the condition of fuzzy information is built, and traditional hybrid intelligent algorithm is improved to solve this model. In the selection of initial solution, roulette heuristic algorithm is adopted to reduce the search range. In the crossover operator, generalized hamming similarity degree is used to distinguish the similarity degree of two chromosomes in order to avoid inbreeding. Duplicate selected and mutated operator is chosen for increasing the convergence speed. A practical example proves the feasibility and high efficiency of the algorithm in dealing with uncertain factors, and different values of confidence of key factors in the fuzzy parameters are selected for comparison and analysis, thereby giving the suggestion on selection.

Key words: Improved hybrid intelligent algorithm, Fuzzy chance constraint programming, Material distribution, Vehicle routing programming