TY - THES A1 - Holeczek, Nikolai T1 - The hazardous materials vehicle routing problem N2 - Hazardous materials (hazmat) have become important goods for satisfying the industrial and customer demand in our modern society. The transportation of these materials is always associated with safety, security and environmental concerns due to the dangerous nature of the cargo. To improve the safety of the transportation process hazmat transportation problems have become a popular research topic in the field of operations research. This thesis contributes to the ongoing research on the hazmat transportation problem. It provides an extensive overview of the existing literature on the hazardous materials transportation problem and offers a new classification extending the existing ones. With particular focus on the hazardous materials vehicle routing problem (HMVRP), this thesis compares different risk models and analyses their influence on the problem outcomes. Additionally, heuristic and meta-heuristic solution procedures are proposed for handling the NP-hard nature of the problem. For this purpose, four different studies are conducted. Study 1 presents a state of the art literature review including over 300 contributions to the hazmat transportation problem. The historical development of the research field is analyzed and the most important journals are identified. A detailed classification focusing on hazmat transportation on public roads is provided. Furthermore, the study identifies research gaps and presents new research opportunities. Study 2 and 3 investigate the effects of path generation in a realistic urban network on the outcomes of the HMVRP. Additionally, different risk models for the HMVRP are compared and their influence on the problem solutions is analyzed. Study 2 proposes a simple but effective heuristic algorithm to solve the HMVRP with load-independent risk models. Study 3 extends the focus and includes load-dependent risk models. The influence of six different risk models on the solution outcomes of the HMVRP is compared and the tradeoff between risk minimization and the minimization of traveled distance is investigated. For this purpose, more than 1,700 problem instances are solved to optimality using CPLEX. In study 4 a hybrid genetic algorithm (HGA) for solving the HMVRP with a load-depending risk model is proposed. The HGA aims to find pareto-optimal solutions for the bi-objective HMVRP when risk and travel distance are addressed simultaneously. The structure of the HGA is explained and experimental findings are presented. In conclusion, this thesis contributes to an improved understanding of the general development in the research field of hazmat logistics and the influence of different risk models on the solution outcomes of the HMVRP. Additionally, heuristic solution methods are proposed and tested for finding compromise solutions when the bi-objective case of risk and distance minimization is addressed. Furthermore, this thesis helps new researchers the access to the field of hazmat logistics as it provides a structured overview of the research field while pointing out research gaps. To address some of the identified research gaps, the thesis provides an extensive analysis of the risk modelling approaches. Thereby, it provides new insights to the basic research on risk modelling for the HMVRP. Finally, to overcome the long computation times of large problem instances heuristic solution approaches are proposed. KW - Hazardous Materials KW - Vehicle Routing Problem Y1 - 2021 UR - https://opus4.kobv.de/opus4-uni-passau/frontdoor/index/index/docId/892 UR - https://nbn-resolving.org/urn:nbn:de:bvb:739-opus4-8927 ER -