Abstract：How to save the cost of collection and transportation is one of the biggest problems in the Urban Garbage Logistics System. In this paper, a model has been set up to minimize the system operation cost, and a genetic algorithm was developed to work this model out. Experimental studies show that the GA generates near optimal solutions very quickly and good –quality solutions can be obtained on an acceptable computational cost. 

Key words: Urban garbage logistics; Location-allocation problem; Genetic algorithm

 1. Introduction

With rapid development of economy, the population of the city dwellers has been increasing and the city become more and more congestive. It also lead to fast increase of annual output of the urban garbage. For example, in 2007 the average amount of domestic garbage produced per day by one ordinary city dweller was about 1.1 kg in Xiamen, China．Accordingly, the collection and transportation cost on garbage rises greatly each year. How to save collection and transportation costs become one of the biggest problems to municipal government in the solid waste management. The key to this problem is to choose proper facility location and plan collection routing.

Finding locations for garbage-collection and disposal sites is, without doubt, a difficult problem involving a range of objectives, environmental constraints, and different public opinions. Due to the lack of comprehensive planning, and the absence of planning controls, most cities in Chinaare operating under indiscipline, haphazardness, and the lack of an adequate and well maintained infrastructure in the urban area. In addition, uncontrolled expansion has resulted in an increase in the average travel distance to be covered by collection vehicles and additional cost to waste management.

So, in section 2 , we will set up models for location-routing problem in urban garbage logistics system. In section 3, we discuss the properties of GA in general terms. Then describe our GA in section 4, and give conclusions in section 5.