A Multi-Objective Decision Model of Traffic Rescue Service Site Location on Road

Abstract

The optimization layout of rescue sites is the premise of implementing traffic resources dispatch and improving rescue efficiency. The multi-objective demands for locating rescue sites on roads cannot be easily satisfied with the traditional single-objective rescue facilities. Based on determined objects used for location, the model of multi-objective decision is proposed to provide suitable schemes of location of rescue sites on road. Integrating traditional models of location, such as p-medians, p-centers, maximum covering location and backup covering, the founded model of multi-objective locations satisfy quick response objects by minimizing the maximum rescue time, satisfy service efficiency objects by maximizing the covering demands and minimizing the total weighted time, and satisfy the demand-oriented objects of serious accidental rescue by maximizing the backup covering demands. Combined with analysis, for example, parametric programming is used to analyze the model, which shows that the model is feasible, and can be used as the theoretical basis for locating traffic rescue sites on roads. 0 INTRODUCTIONS The study of road traffic accident focuses on preventative measures and rescue schemes. The preventative measures mainly include the investigation and renovation of accident black spots, improvement of road conditions, as well as the construction of road safety facilities. The rescue schemes mainly include the rescue association, the resources dispatch, and on-site rescue. Optimizing the location of traffic rescue service sites on roads, which belong to the preventive measures, has not been given enough attention in real works. Location of rescue sites mainly depends on the subjective judgment and experience from decision-makers, a lack of scientific basis. And scholars at home and abroad propose a number of classic models, such as collection covering location model, maximum covering location model, backup covering model, and p-medians and p-centers. Collection covering location is used to identify the minimum number of facilities which can cover all the requirement sites. If there are limited funds, only P facilities can be chosen, and in this case, the process of maximum covering location is used to identify the location of each facility to maximize the population (or other indicators) of covered requirement sites. As the requirement sites, which are served a by