Global Shortest Path Programming using Genetic Algorithms

摘要：

The global shortest path programming (GSPP) has extensive applications in engineering practices. The Steiner tree problem is a nonlinear programming conundrum with fixed points and fictive points and is typical theoretical basis or GSPP. The Steiner minimum tree (SMT) problem can be changed to a combination-optimization problem, a test selection algorithm for the construction of the initial population is proposed correspondingly, and an improved genetic algorithms (GA) is discussed to solve the objective of SMT problem. The simulation shows that the global optimum can be quickly obtained by the improved algorithm. Compared with the visualization experiment approach, the proposed approach can be fulfilled accurately and rapidly and it provides a convenient way and tool for the solution to the practical application problems in engineering fields.

关键词： Shortest path programming Steiner minimum tree(SMT) Combinatorial optimization Genetic algorithm(GA)

作者: Kun YE Zong-Xiao YANG Lei SONG Li-Li Xu

作者单位: Institute of Systems Science and Engineering, Henan University of Science and Technology, Luoyang 471003, China

会议类型: 国际会议

会议名称: 2011 3rd IEEE International Conference on Computer Research and Development(ICCRD 2011)(2011第三届计算机研究与发展国际会议)

会议地点: 上海

会议语种:英文

页码: 75-79

在线出版日期: 2011-03-11（万方平台首次上网日期，不代表论文的发表时间）