Y.P. Li

Bio: Y.P. Li is an academic researcher from University of Regina. The author has contributed to research in topics: Stochastic programming & Farm water. The author has an hindex of 17, co-authored 66 publications receiving 1131 citations. Previous affiliations of Y.P. Li include Beijing Normal University & Shandong University.

ITCLP: An inexact two-stage chance-constrained program for planning waste management systems

Abstract: An inexact two-stage chance-constrained linear programming (ITCLP) method is developed for planning waste management systems. The model is derived by incorporating the techniques of two-stage and chance-constrained programming within a general interval-optimization framework. It can tackle uncertainties presented as both probability distributions and discrete intervals. Moreover, it can be used for analyzing various policy scenarios that are associated with different levels of economic penalties when the promised policy targets are violated. It can also help examine the reliability of satisfying (or risk of violating) system constraints under uncertainty. The developed method is applied to a case of long-term waste management planning. Interval solutions associated different risk levels of constraint violation are obtained. They can be used for generating decision alternatives and thus help waste managers to identify desired policies under various environmental, economic, and system-reliability constraints.

IFMP: Interval-fuzzy multistage programming for water resources management under uncertainty

Abstract: An interval-fuzzy multistage programming (IFMP) method is developed for water resources management under uncertainty. This method improves upon the existing multistage stochastic programming methods by allowing uncertainties presented as discrete intervals, fuzzy sets, and probability distributions to be effectively incorporated within its optimization framework. The IFMP method can adequately reflect dynamic variations of system conditions, particularly for large-scale multistage problems with sequential structures. The uncertain information can be incorporated within a multi-layer scenario tree; revised decisions are permitted in each time period based on the realized values of the uncertain events. Moreover, this method can be used for analyzing various policy scenarios that are associated with different levels of economic consequences when the promised water-allocation targets are violated. A case study of water resources management is then provided for demonstrating applicability of the developed method. For all scenarios under consideration, corrective actions are allowed to be taken dynamically in reference to the pre-regulated policies and the realized uncertainties. The results can help quantify the relationships among system benefit, satisfaction degree, and constraint-violation risk. Thus, desired decision alternatives can be generated under different conditions of supply-demand dynamics.

Mixed interval–fuzzy two-stage integer programming and its application to flood-diversion planning

Abstract: Innovative prevention, adaptation, and mitigation approaches as well as policies for sustainable flood management continue to be challenges faced by decision-makers. In this study, a mixed interval–fuzzy two-stage integer programming (IFTIP) method is developed for flood-diversion planning under uncertainty. This method improves upon the existing interval, fuzzy, and two-stage programming approaches by allowing uncertainties expressed as probability distributions, fuzzy sets, and discrete intervals to be directly incorporated within the optimization framework. In its modelling formulation, economic penalties as corrective measures against any infeasibilities arising because of a particular realization of the uncertainties are taken into account. The method can also be used for analysing a variety of policy scenarios that are associated with different levels of economic penalties. A management problem in terms of flood control is studied to illustrate the applicability of the proposed approach. The results...

The Design and Analysis of Experiments

Abstract: THE DESIGN AND ANALYSIS OF EXPERIMENTS. By Oscar Kempthorne. New York, John Wiley and Sons, Inc., 1952. 631 pp. $8.50. This book by a teacher of statistics (as well as a consultant for \"experimenters\") is a comprehensive study of the philosophical background for the statistical design of experiment. It is necessary to have some facility with algebraic notation and manipulation to be able to use the volume intelligently. The problems are presented from the theoretical point of view, without such practical examples as would be helpful for those not acquainted with mathematics. The mathematical justification for the techniques is given. As a somewhat advanced treatment of the design and analysis of experiments, this volume will be interesting and helpful for many who approach statistics theoretically as well as practically. With emphasis on the \"why,\" and with description given broadly, the author relates the subject matter to the general theory of statistics and to the general problem of experimental inference. MARGARET J. ROBERTSON