A Crop Planning Problem with Fuzzy Random Profit Coefficients

The main purpose of this paper is to present a crop planning problem for agricultural management under uncertainty. It is significant that agricultural managers assign their limited farmlands to cultivation of which crops in a season. This planning is called the crop planning problem and influences their incomes for the season. Usually, the crop planning problem is formulated as a linear programming problem. But there are many uncertain factors in agricultural problems, so future profits for crops are not certain values. A linear programming model with constant profit coefficients may not reflect the environment of decision making properly. Therefore, we propose a model of crop planning with fuzzy profit coefficients, and an effective solution procedure for the model. Furthermore, we extend this fuzzy model, setting the profit coefficients as discrete randomized fuzzy numbers. We show concrete optimal solutions for each models.     

Optimal corrective maintenance contract planning for aging multi‐state system

This paper considers an aging multi‐state system, where the system failure rate varies with time. After any failure, maintenance is performed by an external repair team. Repair rate and cost of each repair are determined by a corresponding corrective maintenance contract with a repair team. The service market can provide different kinds of maintenance contracts to the system owner, which also can be changed after each specified time period. The owner of the system would like to determine a series of repair contracts during the system life cycle in order to minimize the total expected cost while satisfying the system availability. Operating cost, repair cost and penalty cost for system failures should be taken into account. The paper proposes a method for determining such optimal series of maintenance contracts. The method is based on the piecewise constant approximation for an increasing failure rate function in order to assess lower and upper bounds of the total expected cost and system availability by using Markov models. The genetic algorithm is used as the optimization technique. Numerical example is presented to illustrate the approach. Copyright © 2009 John Wiley & Sons, Ltd.     

Warmstarting for interior point methods applied to the long-term power planning problem

The long-term planning of electricity generation in a liberalised market using the Bloom and Gallant model can be posed as a quadratic programming (QP) problem with an exponential number of linear inequality constraints called load-matching constraints (LMCs) and several other linear non-LMCs. Direct solution methods are inefficient at handling such problems and a heuristic procedure has been devised to generate only those LMCs that are likely to be active at the optimiser. The problem is then solved as a finite succession of QP problems with an increasing, though still limited, number of LMCs, which can be solved efficiently using a direct method, as would be the case with a QP interior-point algorithm. Warm starting between successive QP solutions helps then in reducing the number of iterations necessary to reach the optimiser.     

Approximately solving multiobjective linear programmes in objective space and an application in radiotherapy treatment planning

In this paper, we propose a modification of Benson’s algorithm for solving multiobjective linear programmes in objective space in order to approximate the true nondominated set. We first summarize Benson’s original algorithm and propose some small changes to improve computational performance. We then introduce our approximation version of the algorithm, which computes an inner and an outer approximation of the nondominated set. We prove that the inner approximation provides a set of -nondominated points. This work is motivated by an application, the beam intensity optimization problem of radiotherapy treatment planning. This problem can be formulated as a multiobjective linear programme with three objectives. The constraint matrix of the problem relies on the calculation of dose deposited in tissue. Since this calculation is always imprecise solving the MOLP exactly is not necessary in practice. With our algorithm we solve the problem approximately within a specified accuracy in objective space. We present results on four clinical cancer cases that clearly illustrate the advantages of our method.     

东南部欠发达地区县域城乡空间统筹发展的规划思考

随着国内区域经济联动的加强,产业布局的调整升级,以及大区域交通条件的改善,我国城市化经济已经进入了一个＂全球化-区域化＂的新发展时期.东南部欠发达地区的城市化、工业化发展面临着若干重大机遇.通过分析县域城乡空间发展存在的一般性问题和制约因素,提出：东南部欠发达地区的发展应以空间规划作为切入点,通过空间规划与行动集成,将城乡统筹概念落实到县域空间层面上,构建一个综合的发展战略与行动规划.     

Improving biorefinery planning: Integration of spatial data using exact optimization nested in an evolutionary strategy

Biorefineries can provide a product portfolio from renewable biomass similar to that of crude oil refineries. To operate biorefineries of any kind, however, the availability of biomass inputs is crucial and must be considered during planning. Here, we develop a planning approach that uses Geographic Information Systems (GIS) to account for spatially scattered biomass when optimizing a biorefinery’s location, capacity, and configuration. To deal with the challenges of a non-smooth objective function arising from the geographic data, higher dimensionality, and strict constraints, the planning problem is repeatedly decomposed by nesting an exact nonlinear program (NLP) inside an evolutionary strategy (ES) heuristic, which handles the spatial data from the GIS. We demonstrate the functionality of the algorithm and show how including spatial data improves the planning process by optimizing a synthesis gas biorefinery using this new planning approach.     

Media pressures on Welsh language preservation

Despite compulsory school instruction in the Welsh language and strong cultural incentives to acquire the language, the most recent UK Census showed a downward trend in the number of speakers. The asymmetry in explicit language acquisition incentives is here considered to be offset by the media dominance of the English language. This dominance is modeled by the introduction of time-dependent connectivity and infectivity among English speakers into an adapted epidemiological model. Extrapolations up to 2050 are made, this being the announced date of a Welsh Assembly language-planning target of one million Welsh speakers.     

可再生能源系统的不确定性优化模型及求解

结合新提出的满意度方法和混合整数规划方法,给出了多态不确定性环境下可再生能源规划模型.该模型综合描述了多地区、多时期、多品种、多部门之间的可再生能源管理系统的复杂性、系统性、动态性和不确定性.最后的实例求解结果说明该模型能很好地反映能源安全性、系统可靠性与系统成本之间的关系,并能给出不同系统违反水平下的能源配置方式及增容计划,为决策者提供决策参考.     

基于关键因素的国家重大区域规划实施效果评价

以国家重大区域规划中的长三角为实证研究对象,利用加权灰色关联度筛选出与政策效果评价关联性高度相关的政策指标:中央财政专项拨款、中央补助收入、中央固定资产投资额,进而建立政策指标与规划目标的第三产业增加值的对数回归函数,通过过去的数据预测某一特定年份第三产业增加值,并与该年份的实际值进行对比、评价国家重大区域规划的政策效果。本文的特色与创新一是通过灰色关联度剔除与政策效果评价关联度小的指标,筛选出对重大区域规划政策效果有显著影响的关键因素。二是通过时间权向量对政策指标的关联度进行加权,体现时间越近的年份、加权灰色关联度越大,指标越应该保留的思路,保证年份越近的指标数据、对评价结果影响越显著。三是通过历史数据的预测,得到在没有规划政策下、区域自然发展的目标效果,并把其与同一时点、政策实施后的实际效果进行对比,得到政策实施后的政策绩效。实证结果表明应该增大对上海和浙江影响显著的中央财政专项拨款的政策投入,减少对上海和浙江影响不显著的中央固定资产投资额的投入。