Optimization of emergency service operations

Abstract

The thesis concerns the topic of emergency service operations in two areas, focusing on the improvement of the protections of critical transportation infrastructures (CTIs) and optimization of expressway tow truck operations. Recognizing of the importance of the protection of critical infrastructures, a binary integer programming model named probabilistic Fire Ambulance Service Technique (FAST) is developed to simultaneously allocate multiple types of emergency service vehicles among the available fire stations to maximize the coverage of CTIs, subject to the limited resources of service vehicles. As a distinction from previous related research, this study has divided the CTIs into two categories: Highly Critical Transportation Infrastructures (HCTIs) and Low Critical Transportation Infrastructures (LCTIs) with different priorities to receive coverage. For each LCTI, it is typically assumed that a single layer coverage is enough whereas for those HCTIs, multiple layer coverage is given. The study of optimization of expressway tow truck operations is targeted at minimizing the total response time to reach all incidents on expressways. The Expressway Tow Truck Location (EXTL), a binary integer programming model, is introduced to locate tow trucks standby areas with corresponding patrol zones, and deploy limited tow vehicles among these located standby areas. The setting of Singapore has been used as the case study in both the probabilistic FAST model and the EXTL model to examine the feasibility and efficiency of the proposed integer programming models, and the effectiveness of the optimized results. Geographic information System (GIS) has been extensively implemented in the case studies, in terms of data processing and visualization.