Optimization Model of Emergency Evacuation Network Based on Genetic Algorithm

Abstract

Aggregation and dispersion are the normal states. In economic production and social life, the evacuation of people and materials deserves extensive attention. From the perspective of mathematics and economics, arranging a thoughtful evacuation is essential for the best balance between personal satisfaction and cost. In this paper, evacuation is deeply studied by a genetic algorithm;  the balance, cost, and willingness (satisfaction) priority models, which consider both satisfaction and cost, are established.

In this paper, based on the field investigation and questionnaire survey conducted by Oriental Sports Center, overall satisfaction is inferred by the satisfaction of each person in the tested sample, and the time cost from the evacuation point to different reception points is inferred through actual investigation. Based on these data, a balance model is established, and the calculation is performed. The ratio of the total willingness value of the evacuated individuals to the total cost is taken as the function of the optimization objective. When the optimization objective function is complex, the genetic algorithm is used to search for the optimal solution by simulating the process of natural evolution. At the same time, the cost priority and willingness priority models are established to compare the advantages and disadvantages of different evacuation schemes and their applicable situations.

The evacuation of Oriental Sports Center is studied using a genetic algorithm. The objective function value of equilibrium model optimization is 0.2155 (optimal solution), significantly different from willingness priority model optimization (0.0300). After calculating the optimization objective function value and cost value under the conditions of cost priority and willingness priority, a “People-oriented and cost-balanced” suggestion is put forward for a large crowd evacuation scheme.