A real-life application in optimal route planning for the transportation of liquefied petroleum gas (LPG) in Hong Kong was performed to implement the proposed framework. A set of criteria fitting the context of Hong Kong were defined, and various optimal routing solutions with diverse compromise in different objectives were generated. The implementation of the proposed methodologies enables the avoidance of the pitfalls of preference-based techniques and the burden of generating a complete set of possible solutions, and provides decision-makers with an overview of the solution space and the possible trade-offs among the conflicting objectives. The application study demonstrated the effectiveness of the proposed methodologies. In light of the study results and limitations, some recommendations are provided for future research. / Effective and rational routing of DGs is one of the powerful means to mitigate the DG transportation risk. DG transportation involves multiple stakeholders playing different roles and having different objectives that are generally conflicting. The solution of such problem is to search for one or a set of "compromise" solutions rendering the best possible trade-offs for conflict resolution among different objectives. Given the multi-objective nature of the DG routing problem, multi-objective optimization (MOP) becomes a sound framework for analysis and decision-making. / The transportation of dangerous goods (DGs) can significantly affect human life and the environment if accidents occur during the transportation process. Such accidents can result in traffic disruption, fatalities, property and environmental damages. Therefore, safe DG transportation is of paramount importance, especially in high-density-living environments where population and socioeconomic activities are densely distributed over the transportation network. / This research establishes a general framework for optimal route planning for DG transportation in a high-density-living environment. Within the framework, multi-criteria risk assessment and multi-objective route planning can be efficiently solved by novel compromise programming models and high performance algorithms. Non-linearity and non-convexity often exist in the optimal DG routing problem which cannot be solved appropriately by conventional models such as the weighed sum approach. This research has proposed three novel methods to facilitate the generation of a set of optimal solutions on the Pareto front representing various trade-offs among the conflicting objectives. The proposed methodologies give full consideration to decision-makers' inclination and capability in determining the weights for different criteria. The compromise programming procedure allows decision-makers to exercise their preference structures in pursuing desired solutions rendering good compromises among different objectives. The adaptive weighting method approximates the Pareto front with a few suitable solutions to help decision-makers select the most satisfactory route without generating all of them. The genetic-algorithm-based approach uses a set of specifically designed genetic operators to efficiently capture a wide range of Pareto-optimal and near-optimal solutions, from which a decision-maker can choose the most preferred or best compromise one to implement. The diversity of methodologies provides decision-makers with more flexibility in choosing appropriate MOP methods to route DG shipments. / Li, Rongrong. / Adviser: Yee Leung. / Source: Dissertation Abstracts International, Volume: 73-01, Section: A, page: . / Thesis (Ph.D.)--Chinese University of Hong Kong, 2010. / Includes bibliographical references (leaves 189-203). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [201-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract also in Chinese.

<p>Uvođenjem novih tehnologija raste potreba za dodatnim resursima, što se odražava na permanentni porast broja opasnih materija. Industrijski rizik je interpretiran kroz fenomen fragmentacije procesne opreme, dok su transportni rizici analizirani kroz model očekivanja akcidenata usled iskliznuća voza. Neizvesnost fragmentacione procene se kreće oko 12,5%. Visok procenat neizvesnosti transportnih akcidenata pokazuje da pouzdana procena rizika zahteva primenu naprednih metoda, poput Dempster-Shafer teorije.</p> / <p>Introduction of new technologies creates a growing need for additional resources, which affects the permanent increase in the number of dangerous materials. Industrial risk is interpreted through the phenomenon of process equipment fragmentation, while transport risks are analyzed through the model of accidents expectation caused by train derailment. The fragmentation estimates uncertainty is around 12.5%. A high percentage of uncertainties in transport accidents show that reliable risk assessment requires the use of advanced methods, such as Dempster-Shafer theory.</p>

Thesis--University of Oklahoma. / Includes bibliographical references (leaves 25-26).

Thesis (Ph. D.)--Florida State University, 2004. / Advisor: Dr. Andrew Dzurik, Florida State University, College of Engineering, Dept. of Civil and Environmental Engineering. Title and description from dissertation home page (June 18, 2004). Includes bibliographical references.

Thesis (Ph. D.)--University of Texas at Austin, 2000. / Vita. Includes bibliographical references (leaves 292-310). Available also in a digital version from Dissertation Abstracts.

Diss. (sammanfattning) Stockholm : Univ., 2004. / Härtill 4 uppsatser.

Diss. (sammanfattning) Umeå : Univ., 2006. / Härtill 5 uppsatser.

Thesis (Ph.D.)--Hong Kong Baptist University, 2006. / Adviser: Ming Hung Wong. Includes bibliographical references.

Thesis (M.S.)--Worcester Polytechnic Institute. / Keywords: PDE-constrained optimization; O3D; sundance; source inversion. Includes bibliographical references (p. 77-78).

Thesis (MTech (Chemical Engineering))--Peninsula Technikon, Cape Town, 2004 / Current Risk Assessment procedures for the estimation of the acute health impacts resulting from the accidental release of toxic chemicals into the atmosphere involve the definition or construction of a representative accidental release scenario and the use of one or other air quality or dispersion model to estimate ambient air concentrations and exposure durations in the vicinity of the source. Legislation such as the South African Occupational Health and Safety Act, 1993, Major Hazard Installation Regulations, United States Risk Management Plan Rule and the European Union Seveso n, to prevent and or minimize impacts of such events require owners of installations to perform a Risk Assessment if they handle hazardous substances above specified threshold quantities. Mathematical modeling has been widely used to assist with the Exposure Assessment to perform off-site worst-case release analysis. Governmental departments, agencies and local authorities increasingly (but not exclusively) rely on air pollution models for making decisions related to air quality, traffic management, urban planning, and public health. As a result, the model users' community is becoming larger and more diverse. Most of the air quality modeling work has so far been based on the "deterministic" approach of using only set input parameters and specific applications. The selected model provides estimates of averaged concentrations using specific meteorological and emission data sets.