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"A simple transformation of the linear programing model used in land use planning to a goal programing model allows the multiple goals implied by multiple use management to be explicitly recognized. This report outlines the procedure for accomplishing the transformation and discusses problems with use of goal programing. Of particular concern are the expert opinions often required to set up the programing matrix, the need for quantitative goals, the choice of relative weights for the goals, and the lack of explicit trade-offs. The relationships of goal programing to linear programing and the "satisficing" decision model are also discussed. Goal programming is not a panacea for poor planning and must be used with full recognition of its problems."
Existing and impending water shortages argue for improving water quantity and quality management. Groundwater Optimization Handbook: Flow, Contaminant Transport, and Conjunctive Management helps you formulate and solve groundwater optimization problems to ensure sustainable supplies of adequate quality and quantity. It shows you how to more effectively use simulation-optimization (S-O) modeling, an economically valuable groundwater management tool that couples simulation models with mathematical optimization techniques. Written for readers of varying familiarity with groundwater hydrology and mathematical optimization, the handbook approaches complex problems realistically. Its techniques have been applied in many legal settings, with produced strategies providing up to 57% improvement over those developed without S-O modeling. These techniques supply constructible designs, planning and management strategies, and metrics for performance-based contracts. Learn how to: Recognize opportunities for applying S-O models Lead client, agency, and consultant personnel through the strategy design and adaptation process Formulate common situations as clear deterministic/stochastic and single/multiobjective mathematical optimization problems Distinguish between problem nonlinearities resulting from physical system characteristics versus management goals Create an S-O model appropriate for your specific needs or select an existing transferrable model Develop acceptable feasible solutions and compute optimal solutions Quantify tradeoffs between multiple objectives Evaluate and adapt a selected optimal strategy, or use it as a metric for comparison Drawing on the author’s numerous real-world designs and more than 30 years of research, consulting, and teaching experience, this practical handbook supplies design procedures, detailed flowcharts, solved problems, lessons learned, and diverse applications. It guides you through the maze of multiple objectives, constraints, and uncertainty to calculate the best strategies for managing flow, contamination, and conjunctive use of groundwater and surface water. Ancillary materials are available from the Downloads tab on the book page at www.crcpress.com.
At a practical level, mathematical programming under multiple objectives has emerged as a powerful tool to assist in the process of searching for decisions which best satisfy a multitude of conflicting objectives, and there are a number of distinct methodologies for multicriteria decision-making problems that exist. These methodologies can be categorized in a variety of ways, such as form of model (e.g. linear, non-linear, stochastic), characteristics of the decision space (e.g. finite or infinite), or solution process (e.g. prior specification of preferences or interactive). Scientists from a variety of disciplines (mathematics, economics and psychology) have contributed to the development of the field of Multicriteria Decision Making (MCDM) (or Multicriteria Decision Analysis (MCDA), Multiattribute Decision Making (MADM), Multiobjective Decision Making (MODM), etc.) over the past 30 years, helping to establish MCDM as an important part of management science. MCDM has become a central component of studies in management science, economics and industrial engineering in many universities worldwide. Multicriteria Decision Making: Advances in MCDM Models, Algorithms, Theory and Applications aims to bring together `state-of-the-art' reviews and the most recent advances by leading experts on the fundamental theories, methodologies and applications of MCDM. This is aimed at graduate students and researchers in mathematics, economics, management and engineering, as well as at practicing management scientists who wish to better understand the principles of this new and fast developing field.