Multi-objective decision-making model for distribution planning of goods and routing of vehicles in emergency multi-objective decision-making model for distribution planning of goods and routing of vehicles in emergency

Abstract

Emergencies are commonly recognized as conditions that should be addressed in the shortest possible time. The readiness to overcome emergency situations -in places where the necessary measures are anticipated-leads to a quicker response, and reduces the inflicted casualties as well as costs. In the occasion of an emergency, distant areas may be affected while having limited resources available. Hence, the main question here is how the available resources should be distributed among the affected areas. The answer to this question could be helpful in critical situations. In this study, an empirical investigation is conducted in order to develop an optimal resource and vehicle scheduling model to meet the needs of the incident areas whose demands are considered dynamic. In this research, an attempt has been made to develop an executive strategy for resource planning in emergency situations. This integrated model covers issues such as: consideration of the demands heterogeneity and dynamics, distribution planning of goods and routing of vehicles simultaneously, and a multi-objective model based on the general measures necessary in the case of an emergency. Upon the fact that the model was multi-objective, it was solved by ε-constraint method as an exact solution and NSGA-II as a meta-heuristic algorithm. Using the genetic algorithm with acceptable solution time, the ability of the model was confirmed for utilizing in real conditions. The data from 2017 Kermanshah earthquake in Iran was used to examine the accuracy and validity of the model for real-world situation. The results were compared with the real information. These results were considered acceptable by Iranian Red Crescent experts.