安徽省水资源宏观经济优化模型研究

以水资源可持续发展为出发点,探讨了一种可以同时兼顾经济发展、水资源利用和社会效益的多目标水资源宏观经济模型的建立方法,通过引入带权2-模评价函数,将多目标优化问题转变成单目标优化问题。以2002年为现状水平年,对安徽省2010年的产业结构及产业规模进行优化分析。结果表明,多目标模型求得的总用水量较单目标模型明显降低,而两模型优化的产业规模与结构差别不大,体现了高用水效率行业优先发展的要求。     

多目标模糊全局优化设计方法和软件

分析了优化设计在土木工程中应用不够广泛的原因，由此提出了一个能用于工程设计的多目标模糊全局优化设计方法。介绍了按该方法研制的软件ＭＦＤ的功能和性能，以及一个用该软件分析的拱坝体型设计实例。     

Minimum spanning trees made easier via multi-objective optimization

Many real-world problems are multi-objective optimization problems and evolutionary algorithms are quite successful on such problems. Since the task is to compute or approximate the Pareto front, multi-objective optimization problems are considered as more difficult than single-objective problems. One should not forget that the fitness vector with respect to more than one objective contains more information that in principle can direct the search of evolutionary algorithms. Therefore, it is possible that a single-objective problem can be solved more efficiently via a generalized multi-objective model of the problem. That this is indeed the case is proved by investigating the computation of minimum spanning trees.This work was supported by the Deutsche Forschungsgemeinschaft (DFG) as part of the Collaborative Research Center Computational Intelligence (SFB 531) and by the German-Israeli Foundation (GIF) in the project Robustness Aspects of Algorithms.     

产品设计方案的多目标决策分析及其智能支持系统

用模糊多目标决策方法对产品设计方案进行决策分析并设计出相应的智能计算机支持系统，实例证明这一方法在实际应用中是有效的和可靠的。     

考虑多样化需求的诊疗设备维护和患者调度联合优化研究

针对诊疗设备维护和住院患者候诊难以有效协调的问题,建立了联合优化模型。首先,假设设备具有离散的劣化状态,将设备的劣化过程建模为连续时间马尔可夫链;其次,考虑到患者对诊疗设备的不同功能频率需求,以及不同劣化状态对患者治疗时间、费用的影响,以患者就诊顺序、检查策略、修复策略为决策变量建立了设备维护和患者调度模型;最后,采用改进后的非支配排序遗传算法对多目标问题进行了求解。实验结果验证了设备维护与患者调度联合优化模型的有效性。改进后的算法提高了整体和局部的搜索能力,且具有鲁棒性。     

基于IFMOP的玉环市区域水资源配置

引入无概率分布的区间数表示不确定性影响范围,选取经济效益、供需水效率和COD排放量分别构建经济目标、社会目标和环境目标优化函数,构建了玉环市不确定性模糊多目标规划(IFMOP)水资源配置模型,并计算了不确定性解集。结果表明:IFMOP配置计算成果可实现玉环市区域水量水质协调高效利用和社会-经济-生态系统均衡发展;在75%来水保证率下各行业配置总水量不确定性范围为14 375万~15 154万m³。IFMOP水资源配置模型在信息不充分的条件下能够全面使用各类数据信息进行水资源配置,更好地满足水资源在各行业配置过程中的动态管理需求。     

Screening model for assessing ‘cost’ of minimum flow requirements in the Svartå River,Sweden

The minimum flow requirements in the Svartå River in Sweden are directed at maintaining fishlife and providing suitable dilution for waste flows. The implications of varying the minimum flow requirements in the river are examined using a mixed integer optimisation model. The model is formulated as a modified method-of-weights technique with the economic issues of hydro-electricity generation, irrigation and urban water supply placed in the objective function and the minimum flows specified within the constraint set. The integer component of the model is required to model the operating policy at the major flow regulation facility in the system and the restricted validity of the irrigation permits. Application of the model shows that in dry years where competition between minimum flow levels and the other economic uses, is most intense, the levels achieved by the various economic objectives are only slightly reduced even with significant increases in the minimum flow requirements. Variations in minimum flow requirements of up to 45% only produce changes of 10% or less in the economic objectives. The lack of sensitivity of the objective levels is due primarily to the level of control exerted indirectly on the whole system in dry years by the release regulation policy and the restricted validity of the irrigation permits. In normal to wet years these policies are not as restrictive and more choice is available. In such years, however, there is generally sufficient water to satisfy all requirements and allocation is not a critical issue. The model itself is formulated generally so that a range of scenarios beyond those examined specifically in the paper can be considered.     

A Web Server for Designing Molecular Switches Composed of Two Interacting RNAs

The programmability of RNA–RNA interactions through intermolecular base-pairing has been successfully exploited to design a variety of RNA devices that artificially regulate gene expression. An in silico design for interacting structured RNA sequences that satisfies multiple design criteria becomes a complex multi-objective problem. Although multi-objective optimization is a powerful technique that explores a vast solution space without empirical weights between design objectives, to date, no web service for multi-objective design of RNA switches that utilizes RNA–RNA interaction has been proposed. We developed a web server, which is based on a multi-objective design algorithm called MODENA, to design two interacting RNAs that form a complex in silico. By predicting the secondary structures with RactIP during the design process, we can design RNAs that form a joint secondary structure with an external pseudoknot. The energy barrier upon the complex formation is modeled by an interaction seed that is optimized in the design algorithm. We benchmarked the RNA switch design approaches (MODENA+RactIP and MODENA+RNAcofold) for the target structures based on natural RNA-RNA interactions. As a result, MODENA+RactIP showed high design performance for the benchmark datasets.     

基于演化算法的奇偶校验器自动设计*

基于演化算法技术,提出一种新的设计思想,实现奇偶校验器的电路自动设计.实验证明,多目标演化算法具有较少的运算量和较高的效率,能自动设计出使用逻辑门数更少、延时更小的奇偶校验器.