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Emergency response facilities allocation in a transportation network involving hazardous materials (HAZMAT)
(2022) Liazos, Alexandros; Λιάζος, Αλέξανδρος; Athens University of Economics and Business, Department of Management Science and Technology; Mourtos, Yiannis; Zachariadis, Emmanouil; Androutsopoulos, Konstantinos
Enormous volumes of hazardous materials are moving every day all over the world. Some are distributed to people’s homes, while others are transported only between major industries and factories. Nonetheless, their presence within global transport networks is intense, and in the meantime, an accident involving any of them can be serious or even deadly. Theirmanagement, thus, is crucial. This diploma thesis seeks to formulate and solve a bi-objective mixed integer problem location-allocation problem; it also aims to provide the locations in which an operator should place emergency response stations that could deal with an incident involving some hazardous material in a given road segment. The optimal allocation of Emergency Response Facilities is vital; it can prevent accidents before their consequences become dangerous and catastrophic. This model raises three questions; where Emergency Response Facilities shall be located, with which emergency vehicles each of them must be equipped, and to what extent this allocation covers the potential demand, expressed in terms of non-coverage cost. The appropriate parameters, decision variables, objective functions, and constraints are defined. A simple case study of this problem is, later, solved in CPLEX Optimization Studio. Two widely used methods of bi-objective optimization, namely Weighted Sum Method and Epsilon-Constraint Method, are the computational tools of this study, and a Pareto front of non-dominated optimal solutions, is produced by each of these methods. Afterwards, the model’s behavior on alterations of one of its parameters is investigated by examining various scenarios. In the scenarios discussed in the Sensitivity analysis chapter, we decrease or increase a facility's capacity and coverage ratio, alter lower acceptable demand coverage, and examine regions with uneven population distribution. Results for all different methods and scenarios are discussed, and ideas for further future research in this extremely interesting inter-disciplinary field are proposed.