Emergency logistics siting-path question for engineering construction projects based on quantum particle swarm algorithm

Abstract

Emergency material security is the key to post-disaster emergency relief in complex environment engineering construction projects. Aiming at the emergency logistics center site path planning problem, the uncertain parameters of congestion time and maximum rescue time are described using trapezoidal fuzzy numbers, and the emergency logistics site path model of the two-phase engineering construction project is established. A quantum particle swarm optimization model is designed to avoid premature population convergence and maintain population diversity. The particle swarm algorithm uses the quantum spin gate’s rotation angle update to represent the particle velocity update. Taking the engineering construction project in the western mountainous area as an example, the validity and applicability of the model are verified through model comparison and sensitivity analysis. The results of the example show that in the complex environment, the quantum particle swarm algorithm takes 29.35 s in convergence time, and the particle swarm algorithm takes 40.12 s, which is 36.69% higher than the efficiency of PSO. In total cost, the quantum particle swarm algorithm has a total cost of 46,632.40 RMB, and the particle swarm algorithm has a total cost of 48,319.51 RMB, which is 3.62% lower than the cost of PSO. The quantum particle swarm algorithm’s total distance is 550.57 km, and the particle swarm algorithm’s total distance is 579.35 km, 5.23% lower than the total distance of PSO. The model established in this study can scientifically select the location of emergency facilities and formulate the emergency rescue path, reduce the response time of emergency rescue and storage costs, and provide decision support for the scheduling of emergency supplies for engineering construction projects in complex and dangerous areas.