Interactive Genetic Algorithm with Mixed Initiative Interaction for multi-criteria ground water monitoring design

Design of optimal plans for environmental planning and management applications should ideally consider the multiple quantitative and qualitative criteria relevant to the problem. For example, in ground water monitoring design problems, qualitative criteria such as acceptable spatial extent and shape of the contaminant plume predicted from the monitored locations can be equally important as the typical quantitative criteria such as economic costs and contaminant prediction accuracy. Incorporation of qualitative criteria in the problem-solving process is typically done in one of two ways: (a) quantifying approximate representations of the qualitative criteria, which are then used as additional criteria during the optimization process, or (b) post-optimization analysis of designs by experts to evaluate the overall performance of the optimized designs with respect to the qualitative criteria. These approaches, however, may not adequately represent all of the relevant qualitative information that affect a human expert involved in design (e.g. engineers, stakeholders, regulators, etc.), and do not necessarily incorporate the effect of the expert's own learning process on the suitability of the final design. The Interactive Genetic Algorithm with Mixed Initiative Interaction (IGAMII) is a novel approach that addresses these limitations by using a collaborative human-computer search strategy to assist users in designing optimized solutions to their applications, while also learning about their problem. The algorithm adaptively learns from the expert's feedback, and explores multiple designs that meet her/his criteria using both the human expert and a simulated model of the expert's responses in a collaborative fashion. The algorithm provides an introspection-based learning framework for the human expert and uses the human's subjective confidence measures to adjust the optimization search process to the transient learning process of the user. This paper presents the design and testing of this computational framework, and the benefits of using this approach for solving groundwater monitoring design problems.     

Multiobjective invasive weed optimization: Application to analysis of Pareto improvement models in electricity markets

This paper presents a proposal for multiobjective Invasive Weed Optimization (IWO) based on nondominated sorting of the solutions. IWO is an ecologically inspired stochastic optimization algorithm which has shown successful results for global optimization. In the present work, performance of the proposed nondominated sorting IWO (NSIWO) algorithm is evaluated through a number of well-known benchmarks for multiobjective optimization. The simulation results of the test problems show that this algorithm is comparable with other multiobjective evolutionary algorithms and is also capable of finding better spread of solutions in some cases. Next, the proposed algorithm is employed to study the Pareto improvement model in two complex electricity markets. First, the Pareto improvement solution set is obtained for a three-player oligopolistic electricity market with a nonlinear demand function. Then, the IEEE 30-bus power system with transmission constraints is considered, and the Pareto improvement solutions are found for the model with deterministic cost functions. In addition, NSIWO algorithm is used to analyze this system with stochastic cost data in a risk management problem which maximizes the expected total profit but minimizes the profit risk in the market.     

利用开源系统优化数字图书馆的高级应用

在信息急剧膨胀的今天,中国图书馆界已跨入数字图书馆阶段,但图书馆的技术力量相对薄弱,其服务手段和技术仍不能满足需要速成服务的读者,数字图书馆不能仅仅以搜索框的形式被动出现,图书馆人必须改善条件,应用新的技术来应对新的需求。本文将介绍一种技术:Drupal,并在此基础上优化数字图书馆的高级应用。     

面向多商户的第三方电子券系统设计与实现

电子券正成为商家促销的一种新技术手段.在一个已有的定制化电子券系统的基础上,针对服务于多商户的应用背景,对系统的需求进行了重新梳理和流程优化,给出了改造后的系统架构.同时,还对新系统的权限管理与访问控制问题进行了重点分析和设计,引入基于角色的访问控制模型,使之能支持面向多商户的管理.     

基于混沌量子进化算法的单交叉口信号控制

城市道路各交叉口交通信号的配时优化和协同控制直接影响整个城市的交通状况.本文以单交叉口模型的交通信号控制问题为背景,构造了以单交叉口滞留的车辆数最少为目标的优化模型.用混沌量子进化算法进行仿真数据求解,得到实时控制的配时方案,并与其它算法的仿真结果进行比较,结果表明该算法对单交叉口的信号配时优化是非常有效的.     

智能家庭混合能源管理的动态建模与优化

智能电网使家庭由静态的能源消费者向动态参与者转变,需对多种不同的供能设备进行协同优化控制。以电网、光伏发电、太阳能集热器及储能电池4种能源为智能家庭的供给源,以室温控制、热水供应为两大主要服务目标,以最小化能源费用支出为优化指标,建立了家庭能源管理的优化控制模型,并提出基于粒子群算法的智能求解策略。通过对某虚拟家庭的仿真,验证了模型和算法的有效性。     

基于群智能混合算法的物流配送路径研究

针对物流车辆路径优化问题,考虑到基本蚁群算法有收敛速度慢、易陷入局部最优的缺点,采用了一种双种群蚁群算法,在蚁群的基础上引入差分进化(DE)和粒子群算法(PSO)。通过在PSOAS种群和DEAS种群之间建立一种信息交流机制,使信息能够在两个种群中传递,以免某一方因错误的信息判断而陷入局部最优点。通过matlab仿真实验测试,表明该群智能混合算法可以较好地解决TSP的问题。     

锻造产品实现节材降耗生产的计算机技术

锻造过程中的材料消耗往往是很大的，依靠计算机技术可以实现较大幅度的节材降耗。文章阐述了节材降耗的原理，提出了节材降耗的技术手段和具体方法。运用该技术进行生产工艺改造，可节约锻造原材料和能耗10％～30％。     

Sulfamic acid functionalized slag for effective removal of organic dye and toxic metal from the aqueous samples

Surface functionalization of blast furnace slag with sulfamic acid(a zwitterion) was performed for the removal of Cr~(3+) and methylene blue dye(MB) from water samples. The slag functionalization process was optimized using Response Surface Methodology Design. Statistical analysis of the parameters that include the sulfamic acid amount(A), reaction time(B), and temperature(C) revealed that(A) increase had a negative effect on the adsorption of both pollutants by the zwitterion slag, whereas(B) and(C)increase presented a positive impact. At the optimum condition of 2 g sulfamic acid amount, 50 min reaction time and 37 °C temperature, the prepared slag showed a removal efficiency of more than 90% for both Cr~(3+) and MB. Surface characterization by SEM/EDS, FTIR, XPS and surface area analyser, showed an improvement in surface properties and the incorporation of zwitterionic NH_2~+ and S@O groups of sulfamic acid. Adsorption isotherm and kinetic studies conducted with the zwitterion slag showed the adsorption process was suited to Freundlich isotherm model and pseudo-second-order kinetic model.The thermodynamic study conducted revealed the spontaneity of the process based on the calculated negative DG(Gibb's free energy) values. The prepared zwitterion slag offered easy regeneration with dilute HCl solution and showed a considerable removal(Cr3+: 65% and MB: 80%) for both pollutants even after 3 cycles of usage.     

海绵城市建设雨水基础设施优化配置研究进展

气候变化和快速城市化改变了城市生态水文循环过程,加剧了水资源短缺、水环境污染、水生态破坏、暴雨洪涝灾害等城市问题。为获取低影响开发措施（low impact development,LID）/绿色基础设施（green infrastructure,GI）与城市灰色基础设施耦合系统空间优化配置方案以及多目标成本-效益最优曲线,本文系统归纳了不同规划目标导向下新建、改建城区海绵城市建设核心指标与控制要点;针对现有研究中的科学和技术问题,构建了雨水基础设施区域优化配置模式,主要由雨水基础设施性能指标数据库、成本效益定量化及计算机辅助决策三部分构成。探讨了数值计算和模型模拟中典型LID设施的关键参数及其性能指标;基于环境经济学理论分析了海绵城市建设成本和效益指标定量化方法;探索有限成本投入下,改善城市水环境、水生态、水资源、水安全的多目标智能优化算法,结合模型模拟以实现城市生态水文良性循环和可持续发展。