城市生活垃圾收运线路优化模型研究

An optimized model for the municipal solid waste collection and transportation system

在分析目前城市生活垃圾的产生及管理现状后,建立了垃圾收运线路的基本优化模型,并得出了模型实现方法,验证了模型的正确性。在模型的算法实现过程中,采用了目前被广泛应用于解决组合优化问题上的蚁群算法。通过分析算法的特点和相关参数对算法性能的影响,结合垃圾收运具体问题,对算法进行改进,得到了适合垃圾收运的优化算法。

This paper is aimed to present an optimized model for the municipal solid waste （MSW） collection and transportation. As is seen, with the economic growth and population expansion, more and more municipal solid wastes （MSW） are to be moved away and treated properly every day, which calls for the enhancement of more efficient Solid Waste Management （IMSWM）, including the work of all the sections and departments in charge of the waste disposal. As a part of MSW management system, MSW collection and transportation system plays an important role and take the charge of a substantial percentage of the total waste management and disposal. In order to heighten the efficiency of waste collection and transportation, it is of principal importance to choose proper routes to transfer and transport the solid waste to the nearest spots or sites available. Analyzing the current municipal solid waste generation and management status, we can find that it has remained a problem to choose the optimal route for the municipal garbage removal vehicles to choose. This paper, however, has been trying to answer the problem in the following steps： first of all, studying the status quo of the actual problem size; then, establishing an Optimization Model for the Waste Collection and Transportation starting from the basic line and deriving an effective implementation method to verify the appropriateness of the model so as to provide a brand-new solution to such waste collection and transportation route. A highly intensive comparative analysis of the optimal algorithms has been done and the ant colony algorithm has been selected in hoping to achieve the model of MSW collection and transportation, for the new bionic optimization algorithm and the ant colony algorithm prove to be suitable and applicable for the stated problem. In addition, this paper has greatly optimized the collection and transportation route by improving on the ant colony algorithm by analyzing the characteristics and related parameters to increase the algorithm performance and the special algorithm