Expanded Distribution, Transportation Algorithm Research

In the fields such as modern industry, agriculture, business and national defense development, many problems pursuing the maximized profits are relevant to assignment and transportation. Optimization of assignment and transportation tends to involve many aspects, such as time, expense, resource, transport line, engineering factors and so on. In different circumstances and according to various requirements, assignment and transportation, combined with those decisive elements which relates and restricts to each other, will result in different extended problems in response to different purpose. Owing to the particularity of these problems and also the significance of computation efficiency, every kind of extended problems has been adopted its own algorithm. This paper mainly deals with the assignment problem with the shortest time limit and the least cost constraint and optimization of transportation problems with capacity limitation and transshipment, which two belong to extended problems of assignment and transportation. The study has important theoretical and practical significance. Drawing on the relevant experience and achievements, this paper gives some innovation that makes the given algorithm more effective and suitable for use. The main achievements show as follow:1. In the Chapter 3, aimed at extended assignment problems, this research paper mainly studies a kind of problem with the shortest time limit and the least cost constraint. Holding the principal idea of the Floyd algorithm, it proposes a two-stage algorithm, which firstly works out the required shortest time limit to complete all tasks, then based on that, it reconstructs a feasible matrix, and works out the least cost constraint to complete all tasks.2. In the Chapter 4, aimed at the extended transportation problems, this paper mainly studies a kind of transshipment problem with supplies, capacityed storage and sales, and gives an algorithm, which establishes an adjustable matrix of cost by making use of the cost networks within the supplies, storage and sales, then finds an adjustment program of reducing the total freight and optimizes, through repeats the process iteratively, it can finally obtain the optimal solution.