一类模糊运输问题及其混合智能算法

Fuzzy Transportation Problem and Its Hybrid Intelligent Algorithm

研究了一类更加贴近于现实生活的模糊环境下的运输问题,即需求量和供应量均为模糊变量的运输问题.并借鉴针对模糊环境中的优化问题提出的机会约束规划模型和相关机会规划模型的思想,建立了模糊运输问题的数学模型.此外,考虑到模型涉及大量具有复杂性和多样性的模糊变量,设计了一种混合智能算法,即基于模糊模拟的遗传算法来求解模型的近似最优解.最后,数值例子表明算法的有效性和可行性.

The authors investigate a more practical transportation problem under fuzzy environment, that is , capacities of supplies and demands in the transportation problem are fuzzy variables. To obtain a directive decision, the authors construct a mathematical model for the fuzzy transportation problem based chance constrained programming and dependent chance programming in fuzzy environment. In addition, since there are many complex fuzzy variables in the mathematical model, the authors design the genetic algorithm to solve the model based on fuzzy simulation. Finally, they give a numerical example to show the efficiency of the algorithm.