OPTIMIZATION ALGORITHM OF PUBLIC SERVICE FACILITIES LAYOUT IN EARTHQUAKE-STRICKEN AREAS BASED ON SA ALGORITHM

Abstract

The environment in earthquake-stricken areas is complex and changeable. The optimization of public service facility layout usually involves multiple objectives, such as maximizing coverage, minimizing service distance, optimizing resource allocation, etc. The coupling conflict between these objectives weakens the functions of public service facilities in earthquake-stricken areas. To improve the emergency response speed of the earthquake-stricken regions and reduce disaster losses, a simulated annealing (SA) based optimization algorithm for the layout of public service facilities in earthquake-stricken areas is proposed. Considering the public service demand in different stages of the earthquake-stricken area, set the minimum maximum weighted distance, the minimum number of facility points, and the minimum total weighted distance of the service demand point area within the service area of the public service facility point as the objective function, and set constraints such as each demand point is covered by at least one facility point, and the minimum number of public service facility points, build a multi-objective optimization model of public service facilities layout to avoid coupling conflicts between multiple objectives. The SA algorithm is used to solve the multi-objective optimization model of public service facility layout. SA algorithm adopts temperature update function and sets heuristic cooling criteria. Combining the success-failure method and the variable scale method, a new solution is generated using the effective offset. The improved Metropolis algorithm is used to set the acceptance criteria for the solution to obtain the optimal layout result for public service facilities in earthquake-stricken areas. The experimental results show that the algorithm can effectively optimize the layout of public service facilities in earthquake-stricken areas, and improve facility coverage and resource utilization.