Solving a novel two-objective facility allocation-routing problem in large-scale emergencies using a two-stage simulated annealing algorithm

摘要

Large-scale emergencies refer to events like major natural disasters, which lead to tremendous demand for medical supplies in a short period. In such cases, because of limited or disrupted local healthcare vehicles, a bulk of medical aids would have to be supplied by national institutions, and the main priority in logistic planning is to decrease the numbers of victims or ulcerous people as much as possible. In this paper, a novel formulation of facility allocation-routing problem (ARP) is presented. In contrast to most studies developed in large-scale emergency problems, we take into consideration the amount of loss due to service delay and unsatisfied demands. This model is defined based on two objectives: 1) minimising total weighted unsatisfied demands, 2) minimising total weighted delay. A two-stage simulated annealing algorithm is also proposed to solve the problem. Several numerical examples are solved to evaluate efficiency of the model and proposed solution.