Multiobjective optimization of an industrial styrene monomer manufacturing process

Multi-objective optimization of the operation and design of a styrene manufacturing process has been studied with the elitist non-dominated sorting genetic algorithm (NSGA-II). In the first part, the study focused on bi-objective optimization and comparative analysis of three different styrene reactor designs—the single-bed, the steam-injected and the double-bed reactors. The objectives were to simultaneously maximize styrene flow rate and styrene selectivity. In the second part, on the other hand, a tri-objective optimization study was performed involving the entire manufacturing process consisting of the reactor, heat-exchangers and separation units. Only the double-bed reactor was considered in this study for maximizing the styrene flow rate and selectivity and minimizing the total heat duty required by the manufacturing process. Results are presented and discussed in detail.     

A systematic approach to design high-performance feed drive systems

A systematic design methodology for the mechatronic system composed of mechanical and control subsystems is proposed to design high-speed and high-precision feed drive systems. Strict mathematical modeling and identification processes of the subsystems are performed in this paper. Parametric studies and circular motion experiments in the x–y table are conducted to investigate the influence of interactions on the performance of feed drive systems. Based on analyses of the system performance according to design and operating parameters, a nonlinear constrained optimization problem including the relevant subsystem parameters of the feed drive system is formulated. The multi-objective optimization procedure and normalization technique are introduced in the design process. A Pareto optimum solution set is applied to investigate the relationships between objective functions. The effectiveness of the proposed design methodology is verified through numerical case studies.     

求解物流Web服务组合问题的两阶段多目标蚁群算法

针对基于QoS的物流Web服务组合优化问题,提出了两阶段多目标蚁群优化(TMACO)算法。首先,针对原始数据集中存在被支配候选服务而增加算法求解时间的问题,提出了基于Pareto支配的预优化策略;其次,针对属性权重难以确定的问题,提出了不依赖权重的信息素更新策略和启发信息策略;最后,针对基础蚁群算法容易陷入局部最优的问题,提出了懒蚂蚁策略。实验结果表明,TMACO算法具有良好性能,相对于基础蚁群算法、利用解与理想解距离来更新信息素的改进蚁群算法、遗传算法以及用支配程度作为解的个体评价的改进遗传算法,TMACO算法有更高的寻优能力,能够找到更多更优的非劣解。     

利益相关者的水资源配置博弈

水资源的准公共产品属性及其在开发利用中存在的外部性使河流自然流态受到严重的扰动,本文基于非合作博弈博弈论,建立主从关系的用户博弈模型分析河流水资源分配,基于个体效益不能达到帕累托最优状态,采用合作博弈方法,建立水资源用户合作博弈模型。合作博弈增加了总效益,但使得上游用户的效益比非合作时减少,有必要对上游用户进行效益补偿:引入微观经济学的无差异曲线与合作联盟形成的条件构建合作效益分配的可行解集,并提出基于边际贡献的效益分配方法在可行解集中挑选唯一的效益分配解。研究结果表明,合作博弈总效益大于非合作博弈的总效益,达到帕累托最优状态;通过合作效益分配,处于先动优势的上游用户的分配效益大于非合作的效益,有利于行动占先者加入合作联盟。     

Determination of design space and optimization of solar water heating systems

In this paper, a methodology is proposed to determine the design space for synthesis, analysis, and optimization of solar water heating systems. The proposed methodology incorporates different design constraints to identify all possible designs or a design space on a collector area vs. storage volume diagram. The design space is represented by tracing constant solar fraction lines on a collector area vs. storage volume diagram. It has been observed that there exists a minimum as well as a maximum storage volume for a given solar fraction and collector area. Similarly existence of a minimum and a maximum collector area is also observed for a fixed solar fraction and storage volume. For multi-objective optimization, a Pareto optimal region is also identified. Based on the identified design space, the solar water heating system is optimized by minimizing annual life cycle cost. Due to uncertainty in solar insolation, system parameters and cost data, global optimization may not be utilized to represent a meaningful design. To overcome this, a region of possible design configurations is also identified in this paper.     

基于极端降水概率分布的山洪灾害预警指标估算模型研究

针对山洪灾害预警指标确定方法中产汇流机制复杂,多参数不确定性影响因素较大的问题,依据极端降水与山洪灾害内在响应联系,提出以GPD分布为基础耦合小流域内自然因素和人为因素,构建基于极端降水概率分布的山洪灾害预警指标估算模型。选取裴河小流域夏湾组为研究对象,采用时段特征雨量检验法和水位流量反推法与模型计算结果进行对比分析。结果表明:该模型简化预警指标确定过程,合理推求山洪灾害预警指标范围,削弱多参数不确定性影响,计算结果安全可靠,适用于山洪灾害预警预报。基于极端降水概率分布的山洪灾害预警指标估算模型完善预警指标计算理论体系,为山洪灾害预警预报提供技术支撑和经验参考。     

大型复杂跨流域调水工程电站-水库-泵站群多目标优化调度

考虑调水量、发电最大和耗能最小3个目标,建立电站-水库-泵站群多目标优化调度模型。基于参数调整策略、邻域变异和加速策略,提出了求解多目标优化调度模型的综合改进布谷鸟新算法并求解模型,获得了发电、调水、泵站耗能多目标Pareto解集。以引汉济渭大型复杂跨流域调水工程为实例,将该模型与模拟调度模型和NSGA-Ⅱ算法多目标优化调度模型的结果进行比较,结果表明,该优化调度模型的发电、调水、耗能、弃水等各项指标合理,具有相对优势。     

地区间电力市场互联互通相关问题（一）基本模型与社会福利分析

在中国积极推动区域电力市场建设的背景下,提出了互联互通电力市场的概念,分析了电力市场互联互通必须满足的基本条件,研究了可实现帕累托改进的各种互联互通市场模式,在此基础上建立了互联互通市场模型,提出了可实现帕累托最优的市场模式。运用福利经济学的基本定理,比较分析了互联互通市场和统一市场的社会福利,研究结果表明:在完全竞争的假设条件下,互联互通市场和统一市场具有相同的市场效益,且互联互通市场是一种帕累托改进,市场成员有积极性参与市场交易。最后提出了中国电力市场建设先实行互联互通后统一市场的可行改革途径。     

济阳坳陷待发现生物气资源量预测新方法

生物气是特殊成因天然气,由于生成机理尚未明确,成因法难以准确预测其资源量.在对生物气成因类型和生成条件分析的基础上划分了评价单元,提出了基于统计学的待发现生物气资源量预测的新方法,即应用截头移位帕雷托分布模型预测各评价单元待发现生物气藏的规模分布,然后构建三角分布函数预测待发现生物气藏数量,最后用Monte Carlo...