MULTIPLE CRITERIA ANALYSIS FOR WATER QUALITY MANAGEMENT IN THE NITRA BASIN1

ABSTRACT: This paper presents the implementation of one element of a decision support system (DSS) for regional water quality management, applied to the Nitra River Basin in Slovakia. A model-based, aspiration-led methodology for multicriteria decision support has been used for the study. Several reusable, modular software tools have been developed and implemented: a problem-specific generator to produce the core part of the mathematical programming model, tools for the generation and interactive modification of multicriteria problems, and a solver for the resulting mixed-integer optimization problem. Provided in the paper are the following: a complete formulation of the mathematical model (including the imbedded water quality model), a summary of the aspiration-reservation-led multiple criteria optimization approach applied to decision support, and an overview of results that illustrate the applied approach and provide some interesting insights to the case study.     

A robust approach for iterative contaminant source location and release history recovery

Contamination source identification is a crucial step in environmental remediation. The exact contaminant source locations and release histories are often unknown due to lack of records and therefore must be identified through inversion. Coupled source location and release history identification is a complex nonlinear optimization problem. Existing strategies for contaminant source identification have important practical limitations. In many studies, analytical solutions for point sources are used; the problem is often formulated and solved via nonlinear optimization; and model uncertainty is seldom considered. In practice, model uncertainty can be significant because of the uncertainty in model structure and parameters, and the error in numerical solutions. An inaccurate model can lead to erroneous inversion of contaminant sources. In this work, a constrained robust least squares (CRLS) estimator is combined with a branch-and-bound global optimization solver for iteratively identifying source release histories and source locations. CRLS is used for source release history recovery and the global optimization solver is used for location search. CRLS is a robust estimator that was developed to incorporate directly a modeler's prior knowledge of model uncertainty and measurement error. The robustness of CRLS is essential for systems that are ill-conditioned. Because of this decoupling, the total solution time can be reduced significantly. Our numerical experiments show that the combination of CRLS with the global optimization solver achieved better performance than the combination of a non-robust estimator, i.e., the nonnegative least squares (NNLS) method, with the same solver.     

边境贸易发展的环境影响预测及其调控研究——以满洲里市为例

边镜贸易作为我国作为开放的重要组成部分，进展显著。本文在概述我国边境贸易发展所产生的环境问题的基础上，以我国最大的陆边口岸－－满州里市为例，运用灰色预测，动态规划等方法探讨边境贸易与环境保护协调发展的途径。     

污水处理工艺系统优化设计理论的研究与发展

综述了污水处理工艺系统优化设计理论研究的发展历史 ,分析总结了优化设计模型研究的发展规律以及需要解决的关键性问题 ;详细介绍了几个具有典型代表性的非线性系统优化模型的结构及寻优方法 ;从 6个特征方面横向比较了部分优化数学模型的研究成果 ;结合国内研究动态提出了对该领域研究前景的展望     

Decision making with option pricing and dynamic programming: development and application

In this study, an option pricing model and a dynamic programming model are developed. These models contribute to the improvement of the decision making process in two respects. First, these models allow for the own growth rate of mining costs to be incorporated into the analysis. Second, these models are developed to estimate the satisfactory gross revenue for investing, so that these models are helpful in analyzing multi-metal mines.The two models are applied to estimate the satisfactory revenue for investing in the Carlin east gold mine, Nevada, USA. The satisfactory revenue estimated by the option pricing model is found to be $42.2M, while that estimated by the dynamic programming model is found to be $44.4M. Since the revenue calculated on the basis of the current conditions is $36M, then the decision by option pricing and dynamic programming is to wait and not to invest now. Despite the difference between the two models in estimating and applying the discount rate, the two models generate the same decision.     

A dynamic model for intertemporal allocation of old-growth forests in the Pacific Northwest

Across the globe, continued policy debates regarding the management of old-growth forests center around the difficult task of balancing economic and ecological considerations. Though the forests of the Pacific Northwest United States are among the most studied old-growth ecosystems, ecological and economic analyses have yielded public land management directives that remain controversial. Specifically, the recently adopted Northwest Forest Plan lacks explicit goals for maintaining intergenerational equity for the use of forest resources and the diversity of old-growth ecosystems. Unlike previous studies which rely on monetary quantification of costs and benefits, this study develops and applies a conceptual framework for evaluating socially optimal Pacific Northwest old-growth forest utilization strategies. Conditions for the optimal management of old-growth forests are derived using dynamic programming. The objective function synthesizes relevant biological and economic attributes of the old-growth allocation problem. Results in the form of extraction paths are compared given social pressure for consumptive and non-consumptive benefits, as well as different planning horizons, rates of social time preference, and environmental variance. Lengthening the planning horizon results in a vast divergence of optimal policies in the absence of discounting. Extraction rates appear to approach zero as the planning horizon approaches infinity. While higher rates of social time preference increase the rate of extraction, forest stocks remaining at the terminal time period equal levels remaining with a lower discount rate. Increasing environmental variance results in a higher level of stock remaining at the terminal time period. This analysis, while specific to the old-growth controversy of the Pacific Northwest, does provide general guidelines for addressing similar problems of multiple uses of natural areas, particularly where such uses are mutually incompatible, or where one use may be irreversibly destructive to another.     

湖北省土地利用减碳增效系统仿真及结构优化研究

土地利用变化是引起碳排放的重要原因之一,土地经济效益是利用土地的目标之一,如何通过优化土地利用结构实现土地利用减碳增效是值得研究的重要问题。基于系统结构与功能相互作用的视角,梳理复杂系统内变量间的反馈关系,运用系统动力学(SD)进行建模,将约束条件纳入到多目标规划(MOP)中,实现MOP与SD模型整合,进行系统仿真并得出优化后2020年湖北省土地利用结构。结果显示,利用SD-MOP模型能够实现减碳增效目标下土地利用结构优化,与2008年真实值相比,耕地、林地、牧草地及建设用地分别增加了0.33×10~4、30.17×10~4、0.08×10~4和16.37×10~4 hm~2,其他农用地及未利用地分别减少7.23×10~4、33.15×10~4 hm~2;与无约束SD单模型仿真相比,土地利用碳排放量减少了58×10~4 t,经济效益年增长率维持在3.58%,优化方案具有可行性。SD-MOP模型优化的土地利用结构符合区域可持续发展要求,兼顾了土地利用碳减排和经济效益增长的双重目标,能为区域土地资源优化配置提供参考。     

滑坡预测的改进前馈网络方法研究

作者提出了滑坡位移预测的一种改进前馈网络方法——目的规划法,与通常的前馈网络方法相比,该方法改进了网络的准则函数,降低了网络的灵敏度,改善了网络的泛化性能,提高了滑坡位移的预测精度。同时它是一种面向数据的方法,适合于不同地区不同条件下滑坡的预测。清江隔河岩库区滑坡和卧龙寺滑坡的实例研究表明了该方法的可行性及有效性。     

结构分析中模拟与仿真技术研究

由于像洪水、水灾、地震这样一类自然灾害的原型重复试验几乎是不可能的,因此计算机仿真技术在这一领域的应用具有重要的意义。本文探索了土木工程中模拟与仿真的概念、特征及实现途径,阐述了关于仿真智能化、可视化的技术细节及仿真的基本思路;结合面向对象程序设计（OOP）概念,提出了结构分析程序设计的原则及标准。在此基础上,编写了基于Windows的结构有限元分析软件SmartSEA.