The Optimization Solution in the Ordering and Transporting of Steel Tube Based on Genetic Simulated Annealing Algorithm

It's a complex nonlinear programming problem to find the optimization parameter in the ordering and transporting of steel tube. In this paper a second time programming model for ordering and transporting of steel tubes is developed for nonlinear relation between transport cost and path length, demand of destinations and unknown price of goods. The method by means of genetic algorithm to solve the model has been discussed. On the basis of analyzing the disadvantages of genetic algorithm approach, a new method has been proposed, which is a hybrid of genetic algorithms and simulated annealing. The experimental result shows that this method, which is called genetic simulated annealing approach, is feasible and efficient for finding the optimum parameter in the ordering and transporting of steel tube and provides a good way to solve ordering and transporting optimization.

1. Introduction

Description of Transport Optimization Problem: Laying a linear pipeline of (Fig.1). To calculate the minimum cost, we suppose there are 7 steelworks that can produce this kind of steel pipelines (each of the steelworks have different production capacity and price, also it should produce more than 500 units if it take on the production (for the easy calculation, lKm steel pipeline is 1 unit)). Aim at this problem, we developed a nonlinear constrained optimization model. Since there are so many variables and constraints in the model, it is very difficult to solve the problem with traditional methods, such as Lagrangian, Feasible direction, various outer points penalty function and so on.