Development of robust optimization methodologies for environmental systems management under uncertainty

Environmental pollution and resource-scarcity problems, associated with rapid social and economic development, have been of critical concern to both national and local governments worldwide for many decades. Identification of decision schemes, with sound environmental and socio-economic efficiencies, is desirable to promote effective environmental management practices. However, environmental management systems are often associated with a variety of complexities and uncertainties being further amplified with not only interactions and dynamics among various sub-systems but also by their associations with economic penalties when various overriding policies are violated. Therefore, the development of effective and robust systems analysis methodologies, capable of addressing the above complexities, are desired.;The major achievements of this research are as follows: (1) A set of innovative methodologies regarding inexact robust optimization have been advanced, which (a) improve upon the existing robust optimization methods by taking into account highly uncertain information under multiple uncertainties, and also (b) improve the conventional systems analysis methods by incorporating the concept of robust optimization within inexact programming framework. Applications of the developed methods to a number of decision-making problems have demonstrated their practical applicability to comprehensive environmental management systems. (2) The developed IFRDP and CCIFRDP methods represent new attempts to robustly tackle multiple uncertainties and system dynamics within a general dynamic programming framework. (3) An IRTSO model has been developed to support the environmental management of the Heshui River Basin, China. The results can provide valuable inputs for (i) adjustment of the existing environmental management schemes in order to satisfy the basin's sustainable development goals, (ii) long-term planning of the basin's environmental management system, and (iii) the generation of desired policies in terms of regional socio-economic development and environmental protection.;In this dissertation research, a set of inexact robust optimization methods have been developed and applied to the management of environmental systems. They include the following elements: (a) an interval-parameter fuzzy robust programming (IFRP) method for the optimal planning of waste-flow allocation, (b) an inexact robust optimization model for water quality management, (c) an interval fuzzy robust dynamic programming (IFRDP) method for capacity planning of waste management systems, (d) a chance-constrained interval fuzzy robust dynamic programming (CCIFRDP) method for energy and environmental management, (e) an inexact fuzzy-robust two-stage stochastic programming (IFRTSP) method for regional air quality management, and (f) an inexact robust two-stage optimization (IRTSO) model for environmental management of the Heshui River Basin, Jiangxi, China. The developed methodologies can assist in providing decision supports for managing a variety of environmental problems under uncertainties.