第三，将地图界面、Google Maps Server服务、遗传算法进行整合，实现用户输入多目的地地点后，Google Maps Server进行两点间的地理数据分析，将数据回传给系统遗传算法模块，遗传算法通过对数据进行分析、计算得出一条最优路径序列，然后将路径序列再次回传给Google Maps Server，从而在地图上显示出最优路径序列。
The logistical development of agricultural goods and materials in China, which is known as a large agricultural country, played an important role in the agricultural field of economy. The reduction of logistical costs largely stimulated the development of the agricultural economy. In order to reduce the cost of logistics transportation the effective planning of the logistics transportation paths was quite necessary and important.
In this paper, we used the mathematical model of the traveling salesman problem (TSP) by implementing genetic algorithms to resolve the path planning problem and with the application of this algorithm, integrated with a map display function, we provided users with a complete logistical picture and route path planning system.
Genetic algorithm was an intelligent optimization algorithm which is derived from biology genetics. It made a directional change in the entire population by means of selection, exchange and variation of gene sequences.
The main content and contributions of the study were as follows:
Firstly, with the help of Google Maps services, we provided our customers with both information inquiry to a single location and a path query to dual location services.
Secondly, users could solve specific path query problems with genetic algorithms and effectively gained actual results through appropriate strategies of gene selection, mutation and genetic crossover as well as a series of genetic algorithm parameters.
In addition, the combination of the map interface Google Maps Server service and the genetic algorithm made it possible to input multiple-destination locations for users. The Google Maps Server conducted geographic data analysis between two points and sent back data to the systems genetic algorithm module. Following the data analysis then genetic algorithms calculated an optimal path sequence and returned it to the Google Maps Server which finally resulted in showing the optimal path sequence on the map.
In this study, our successful connection of research and practical application of this algorithm largely satisfied our customers with dramatically improved efficiency of logistics and distribution. It was recommended that the ideal delivery destinations should be controlled as fewer than 10.