A new model for road network repair after natural disasters: Integrating logistics support scheduling with repair crew scheduling and routing activities

Abstract

Road network restoration in affected areas is critical for search and rescue, evacuation, and relief distribution after a natural disaster. However, the accomplishment of post–disaster road network repair (PDRNR) performed by repair crews depends on an effective and efficient logistics support scheduling (LSS). However, existing studies on PDRNR have not taken into account the repair crew routing problem, which will affect the status of the road network interactively. To fill the gap, we focus on integrating LSS with the repair crew scheduling and routing problem (RCSRP) for PDRNR. A novel non–linear programming model is developed and an intertwined two–stage heuristic algorithm (ITSHA) is proposed for the LSS–RCSRP. In the first stage, an improved bacterial colony chemotaxis optimization algorithm (IBCCOA) is employed to determine the repair crew scheduling. In the second stage, LSS for each block and repair crew routing are determined in line with the repair crew scheduling and road network status. We validate and test the effectiveness of IBCCOA by solving some classical vehicle routing problems of different scales. To illustrate the applicability and effectiveness of the proposed model and ITSHA, we conduct a case study abstracted from the 2008 Wenchuan earthquake. The results show that by considering LSS, repair delays can be reduced by 45.71%, while the average restoration ratio can reach as high as 99.40% during the “golden 72 hours.”