Research On The Evolutionary Multiple-Object Routing Optimizations

The problem of multi-objective optimizations has always been considered as a difficult and hot one in engineering and science fields. Classical approaches have been given out before Genetic Algorithms was applied in this field. It has so many shortages in Classical approaches yet. The shortages were overcome by Genetic Algorithms. So it will be the forward trend to solve the problem of multi-objective optimizations by Genetic Algorithms.It is one of the most familiar problems in net-design to solve routing problem. That is, to find the shortest or cost-lowest route between two points. The route can be exactly found out by using classical Dijkstra method. But the method uses too much cost of time and space. The phenomena is reduced by using Genetic Algorithms.Two aspects must be considered in solving multiple-object routing optimizations by using Genetic Algorithms. As follows: firstly, how to give the choice press in solving the problem of multi-objective optimizations, secondly how to operator on the route in routing problem by using Genetic AlgorithmsBased on some internal and foreign literatures, some basic theories and methods were studied in this text about Genetic Algorithms, multi-objective optimizations and routing problem with Genetic Algorithms in them. A new approach and the relevant experiment were given. The main work was expounded as follows:Firstly, we introduced the basic theories, means and flow about Genetic Algorithms, and Genetic Algorithms in multi-objective optimizations was also included.Secondly, routing- optimizations was also solved by using Genetic Algorithms and the same time validated with Dijkstra method.Lastly, based on the weight in weighted-sum approaches before, we gave some improvement to get the weight.