The Optimal Model And Algorithm Of The Transportation Problem Under The Uncertain Environment

The classical transportation problem(TP) refers to the allocation problem in which the goods are transported from the manufacturer to the distributor at minimum cost. In practice,in order to reach different purposes, there are the transportation problem which have the optimization goals of the shortest travel time, or the biggest transportation volume and so on. If we search for the multiple objectives at the same time, then there is the multi-objective transportation problem. In the real progress of production and transportation, usually, there is uncertainty being based on the weather, production planning, market demands, and road conditions, therefore, the transportation problem under the uncertain environment has become a hot spot in recent operations management field.Firstly, by using the modeling methods of uncertain programming and stochastic programming, and assuming that the transportation times are uncertain variables, the demands of transportation are random variables, the transportation cost is a function of transportation time, we study the problem of this kind. Under the budget constraints of capital, we develop the uncertain stochastic programming model to minimize the transportation time. Based on the characteristics of the model, the corresponding heuristic algorithm is designed. Thus, combined the model and algorithm, we research an practical example. And the results show that the model and the algorithm are promising.Secondly, considering the decisions of two aspects of the production and transportation comprehensively, the goal is to make the total of production and transportation to be lowest. Under the conditions that the demands are random variables,the variant costs and the amounts of the consumption of raw materials that every manufacturer produces unit product are all uncertain variables, the model of uncertain and stochastic programming of production and transportation is developed. Finally, a practical example shows the effectiveness of the model developed.