Solving the probabilistic reserve selection problem

The Reserve Selection Problem consists in selecting certain sites among a set of potential sites for biodiversity protection. In many models of the literature, the species present and able to survive in each site are supposed to be known. Here, for every potential site and for every species considered, only the probability that the species survives in the site is supposed to be known. The problem to select, under a budgetary constraint, a set of sites which maximizes the expected number of species is known in the literature under the name of probabilistic reserve selection problem. In this article, this problem is studied with species weighting to deal differently with common species and rare species. A spatial constraint is also considered preventing to obtain too fragmented reserve networks. As in Polasky et al. (2000), the problem is formulated by a nonlinear mathematical program in Boolean variables. Camm et al. (2002) developed a mixed-integer linear programming approximation that may be solved with standard integer programming software. The method gives tight approximate solutions but does not allow to tell how far these solutions are from the optimum. In this paper, a slightly different approach is proposed to approximate the problem. The interesting aspect of the approach, which also uses only standard mixed-integer programming software, is that it leads, not only to an approximate solution, but also to an upper limit on the true optimal value. In other words, the method gives an approximate solution with a guarantee on its accuracy. The linear reformulation is based on an upper approximation of the logarithmic function by a piecewise-linear function. The approach is very effective on artificial instances that include up to 400 sites and 300 species. Within an average CPU time of about 12 min, near-optimal solutions are obtained with an average relative error, in comparison to the optimum, of less than 0.2%.     

Inexact credibility constrained programming for environmental system management

This study proposed an inexact credibility constrained programming (ICCP) to deal with multi-formats of uncertainties in parameters and variables for an agricultural water planning system. The study system includes three subareas with different crop distributions. The redundant water in the wet season can be stored in the reservoir and utilized in the dry season. The ICCP method can reflect not only inexact uncertainties in the objective function, variables and parameters, but also fuzzy uncertainties in the right-hand side. Interval credibility levels which represent satisfaction degrees of the constraints can be analyzed. Scenario analysis is conducted to analyze possible events in wet and dry years. The resulting solutions can provide stable intervals for the objective function and decision variables with different levels of risk when violating the constraints.     

Novel operations research methods for efficiently determining irreplaceable sites for conservation

We examine the irreplaceability of sites in the context of the species set covering problem and the maximal covering species problem. We show that a succession of 0-1 programming problems can be solved to quickly determine the set of irreplaceable sites. For the widely available Oregon data set, we find a general lack of trend in the number of irreplaceable sites with the number of sites available for selection used. Moreover, we observe that irreplaceability at one level of resource may not be a predictor of irreplaceability at a higher or a lower level of resource. Finally, we investigate the economic value of irreplaceable sites by trial removals of those sites. This paper is dedicated to the memory of Dr. Charles S. ReVelle.     

城市新经济开发区大气环境容量计算及分配方法研究

随着改革开放步伐的加快，城市开发区也随之蓬勃发展起来。城市新经济开发区的大气环境容量计算及分配是开发区区域环境影响评价的一个重要内容。介绍了建立在网格基础之上的大气污染物总量控制方案的制定方法，引入了污染物扩散转移矩阵概念，并结合广州科学城大气环境总量控制规划，将该方法应用在城市开发区大气环境容量计算及管理中，最后本着公平分配的原则，注重经济效果和社会效率，达到环境保护的目标，提出了一种基于企业占地面积的容量分配方案。按照地块面积划分总量方法不但适应了开发区的动态的发展需要，而且将环境因素引入企业的决策过程。所介绍的方法将对新经济开发区大气环境容量计算及分配具有一定的借鉴作用。     

Modeling methods for managing raw material compositional uncertainty in alloy production

Operational uncertainties create disincentives for use of recycled materials in metal alloy production. One that greatly influences remelter batch optimization is variation in the raw material composition, particularly for secondary materials. Currently, to accommodate compositional variation, firms commonly set production targets well inside the window of compositional specification required for performance reasons. Window narrowing, while effective, does not make use of statistical sampling data, leading to sub-optimal usage of recycled materials. This paper explores the use of a chance-constrained optimization method, which allows explicit consideration of statistical information on composition. The framework and a case study of cast and wrought production with available scrap materials are presented. Results show that it is possible to increase the use of recycled material without compromising the likelihood of batch errors, when using this method compared to conventional window narrowing. This benefit of the chance-constrained method grows with increase in compositional uncertainty and is driven by scrap portfolio diversification.     

Study on the Programming Standard for Ecological Rescue in General Land Use Planning

This paper aims at establishing the operation idea based on the analysis of the connotation,principles and reference indexes for programming standard for ecological rescue.The paper puts forward that the programming standard should take into account the natural,social and economic reference indexes,and modifies the scale and distribution of the ecological rescue according to the order of ecological safety,social safety and economic development.The paper suggests that the land planning department should strengthen the study and datum accumulation in order to establish the technology regulations of programming standard of the ecological rescue.     

Optimizing the horizontal structural diversity in uneven-aged northern hardwood stands

Two mathematical programming formulations are presented which allow the determination of diameter distributions that maximize the diameter class diversity in uneven-aged northern hardwood stands. Distributions generated from these models were found to be comparable from a management standpoint and could be incorporated into existing linear programming models as alternative management scenarios. The models presented here provide an initial framework for quantitatively addressing the requirements of the US National Forest Management Act in matters of diversity in the planning process.     

An interval type-2 fuzzy stochastic approach for regional-scale electric power system under parameter uncertainty

In this study, an interval type-2 fuzzy stochastic linear programming method (IT2FSLP) is developed to support regional-scale electric power system (REM) planning. The IT2FSLP-REM model is based on an integration of interval type-2 fuzzy sets boundary programming and stochastic linear programming techniques enable it to have robust abilities to the deal with uncertainties expressed as type-2 fuzzy intervals and probabilistic distributions within a general optimization framework. Moreover, it can reflect dynamic decisions for energy supply and energy conversion processes, as well as provide capacity expansion options with multiple periods. The developed model is applied to a case of planning regional-scale energy and environmental systems to demonstrate its applicability. Based on a two-step solution algorithm, reasonable solutions have been obtained, which reflect tradeoffs among economic cost, environmental requirements, and energy-supply security. Thus, the lower and upper solutions of IT2FSLP-REM would then help energy authorities adjust or justify allocation patterns of regional energy resources and services.