Estimation of distribution algorithm enhanced particle swarm optimization for water distribution network optimization

The optimization of a water distribution network (WDN) is a highly nonlinear, multi-modal, and constrained combinatorial problem. Particle swarm optimization (PSO) has been shown to be a fast converging algorithm for WDN optimization. An improved estimation of distribution algorithm (EDA) using historic best positions to construct a sample space is hybridized with PSO both in sequential and in parallel to improve population diversity control and avoid premature convergence. Two water distribution network benchmark examples from the literature are adopted to evaluate the performance of the proposed hybrid algorithms. The experimental results indicate that the proposed algorithms achieved the literature record minimum (6.081 M$) for the small size Hanoi network. For the large size Balerma network, the parallel hybrid achieved a slightly lower minimum (1.921M€) than the current literature reported best minimum (1.923M€). The average number of evaluations needed to achieve the minimum is one order smaller than most existing algorithms. With a fixed, small number of evaluations, the sequential hybrid outperforms the parallel hybrid showing its capability for fast convergence. The fitness and diversity of the populations were tracked for the proposed algorithms. The track record suggests that constructing an EDA sample space with historic best positions can improve diversity control significantly. Parallel hybridization also helps to improve diversity control yet its effect is relatively less significant.     

Optimization of thermophilic anaerobic-aerobic treatment system for Palm Oil Mill Effluent (POME)

Optimization of an integrated anaerobic-aerobic bioreactor (IAAB) treatment system for the reduction of organic matter (Chemical Oxygen Demand (COD), Biochemical Oxygen Demand (BOD) and Total Suspended Solids (TSS) concentrations) in Palm Oil Mill Effluent (POME) to legal standards with high methane yield was performed for the first time under thermophilic condition (50°C–55°C) by using response surface methodology (RSM). The experiments were conducted based on a central composite rotatable design (CCRD) with three independent operating variables, organic loading rates in anaerobic compartment (OLR_an) and mixed liquor volatile suspended solids (MLVSS) concentration in anaerobic (MLVSS_an) and aerobic compartments (MLVSS_a). The optimum conditions for the POME treatment were determined as OLR_an of 15.6 g COD·L^-1·d^-1, MLVSS_an of 43100 mg·L^-1, and MLVSS_a of 18600 mg·L^-1, where high aerobic COD, BOD and TSS removal efficiencies of 96.3%, 97.9%, and 98.5% were achieved with treated BOD of 56 mg·L^-1 and TSS of 28 mg·L^-1 meeting the discharge standard. This optimization study successfully achieved a reduction of 42% in the BOD concentrations of the final treated effluent at a 48% higher OLR_an as compared to the previous works. Besides, thermophilic IAAB system scores better feasibility and higher effectiveness as compared to the optimized mesophilic system. This is due to its higher ability to handle high OLR with higher overall treatment efficiencies (more than 99.6%), methane yield (0.31 L CH₄·g^-1 COD_removed) and purity of methane (67.5%). Hence, these advantages ascertain the applicability of thermophilic IAAB in the POME treatment or even in other high-strength wastewaters treatment.     

An integrated model for structure optimization and technology screening of urban wastewater systems

The conventional approach to wastewater system design and planning considers each component separately and does not provide the optimum performance of the entire system. However, the growing concern for environmental protection, economic efficiency, and sustainability of urban wastewater systems requires an integrated modeling of subsystems and a synthetic evaluation of multiple objectives. In this study, a multi-objective optimization model of an integrated urban wastewater system was developed. The model encompasses subsystems, such as a sewer system, stormwater management, municipal wastewater treatment, and a wastewater reclamation system. The non-dominated sorting genetic algorithm (NSGA-II) was used to generate a range of system design possibilities to optimize conflicting environmental and economic objectives. Information from a knowledge base, which included rules for generating treatment trains as well as the performance characteristics of commonly used water pollution control measures, was utilized. The trade-off relationships between the objectives, total water pollution loads to the environment, and life cycle costs (which consist of investment as well as operation and maintenance costs), can be illustrated using Pareto charts. The developed model can be used to assist decision makers in the preliminary planning of system structure. A benchmark city was constructed to illustrate the methods of multi-objective controls, highlight cost-effective water pollution control measures, and identify the main pressures on urban water environment.     

基于地表沉陷控制的膏体充填材料的性能优化研究

充填材料性能是充填开采控制地表沉陷的一个重要因素,为克服传统充填材料性能优化试验耗时长、成本高、人为误差较大的缺点,探索将传统正交试验与模糊决策相结合进行充填材料性能优化。基于L9(33)正交试验,确定了S1~S55组充填材料性能优选方案。在综合分析充填材料性能影响因素的基础上,建立充填材料性能优化指标体系,构建AHP-FUZZY模糊综合优选模型对方案进行比选,并分析了正交试验中各因素水平变化对最优方案的敏感性。结果表明:膏体充填材料性能最优方案为“S4”即水泥含量15%,灰矸比1∶2,质量浓度75%,决策结果与试验结果相符,且“灰矸比”对充填材料性能优化的敏感性程度最高,在实际膏体充填开采中要严格控制粉煤灰和煤矸石掺量。     

故障树法和改进PSO-PNN网络的电梯故障诊断模型

针对电梯故障问题,提出一种将故障树分析法、改进的粒子群优化算法和概率神经网络相结合的方法用于电梯的故障诊断。以电梯的安全回路系统为例,用故障树法对回路进行分析,获得训练样本与故障类型;使用粒子群算法对概率神经网络的平滑因子进行优化,在优化过程中,针对粒子群算法存在易陷入局部最优的缺陷,提出对惯性权重的改进策略;采用相对误差对诊断效果做出评估,并与传统的概率神经网络和基本粒子群算法优化的概率神经网络在各种故障类型输出和最大相对误差等方面进行比较,结果表明:该模型能够有效诊断电梯故障。     

基于鲸鱼优化算法与投影寻踪耦合的云南省初始水权分配

论文基于公平性、效率性和可持续性原则,选取水资源开发用率等17个分水指标建立云南省初始水权分配指标体系,运用投影寻踪（Projection Pursuit, PP）技术确定云南省各州市初始水权分配水量。针对PP技术最佳投影方向难以确定的不足,利用一种新型群智能算法——鲸鱼优化算法（Whale Optimization Algorithm, WOA）寻优PP模型最佳投影方向,构建WOA-PP耦合的初始水权分配模型。通过6个典型测试函数对WOA进行仿真验证,仿真结果与文化算法（Cultural Algorithm, CA）、差分进化（Differential Evolution, DE）算法、混合蛙跳算法（Shuffled Frog Leaping Algorithm, SFLA）、布谷鸟搜索（Cuckoo Search, CS）算法、粒子群优化（Particle Swarm Optimization, PSO）算法和人工蜂群（Artificial Bee Colony, ABC）算法的寻优结果进行比较。结果表明：1）无论是单峰还是多峰函数,WOA能够探索不同的搜索空间,具有良好的开发和勘探能力,对Sphere等6个函数的寻优精度高于CA、DE、SFLA、CS、PSO和ABC算法,表现出较好的寻优精度、收敛速度、全局寻优能力与收敛稳定性。2）从WOA-PP模型初始水权分配结果及目前实行的综合法水量分配结果对比来看,2015年昭通、丽江、临沧、红河、文山、怒江两种方法的分配结果相差最小,在0.11亿~0.41亿m³之间;玉溪、普洱、大理、德宏和迪庆两种方法的分配结果相差最大,在2.06亿~4.38亿m³之间;其余州市两种方法的分配结果在1.12亿~1.61亿m³之间。2020年保山、昭通、丽江、临沧、红河、文山、怒江两种方法的分配结果相差最小,在0.02亿~0.41亿m³之间;昆明、玉溪和德宏两种方法的分配结果相差最大,分别为5.89亿、5.66亿和3.54亿m³;其余州市两种方法的分配结果在1.89亿~2.85亿m³之间。3）论文提出的初始水权分配模型及方法具有一定的可操作性和有效性,可为区域初始水权分配提供新的思路和方法。     

不同好氧/缺氧时长联合分区排泥优化生活污水短程硝化反硝化除磷颗粒系统运行

采用生活污水接种人工配水下成熟短程硝化反硝化除磷颗粒,通过不同好氧/缺氧时长联合分区排泥优化调控短程硝化反硝化除磷系统运行.结果表明,调控好氧/缺氧时长联合分区排泥可实现系统的稳定运行.后期稳定期出水COD浓度在50mg·L^-1以下,出水TN浓度低于15mg·L^-1,TN去除率达83%左右并保持平稳,出水P浓度均在0.5mg·L^-1以下,平均去除率为93.72%.同时,分区排泥（70%顶部污泥和30%底部污泥）可作为筛选微生物的途径,维持了良好的亚硝化和除磷性能,使粒径分布更为集中,并保证氨氧化菌（ammonia oxidizing bacteria,AOB）和反硝化聚磷菌（denitrifying phosphate accumulating organisms,DPAOs）的生长优势.缺氧时长的增加提高了缺氧异养菌的生长速率,使得缺氧异养菌分泌出更多的EPS,确保了颗粒污泥性状的改善和后续维持稳定.     

双出口疏散吸引区域模型建立与模拟分析

为研究建筑体内人员疏散的出口选择行为,提出基于元胞自动机的人员疏散模型。以学校常见的双出口教室为例进行研究,建立双出口疏散吸引区域模型,得出人员密度较低和较高时疏散吸引区域边界的函数表达式,指出人员密度较高时,边界函数基本满足边界到出口距离的平方之比等于出口的宽度之比;通过对出口宽度、人员数量和出口位置等参量进行仿真分析,充分验证了提出的双出口疏散吸引区域模型的合理性;研究结果有助于合理分配疏散人员,充分发挥建筑疏散的潜在能力。     

大气污染防治综合决策支持技术平台典型城市应用研究

以典型城市济南市为研究对象,利用大气污染防治综合决策支持技术平台(简称“技术平台”)综合评估了济南市《2018年大气污染治理“十大措施”实施方案》(简称“‘十大措施’”)的实施效果,并进一步基于特定空气质量目标〔济南市2018年ρ(PM_2.5)、ρ(O₃)同比2017年分别下降20%、8%〕开展大气污染防治策略寻优及费效评估.结果表明:①“十大措施”实施后,SO₂、NO_x、VOCs、一次PM_2.5减排率分别为39%、24%、42%、41%,该情景在2017基准年气象条件下可使济南市2018年ρ(PM_2.5)同比下降19%,新增治污成本约4.70×108元,效益-成本比约1.40;单位减排成本最低的本地扬尘源减排对ρ(PM_2.5)下降的贡献率最大,建议济南市下一阶段应进一步强化扬尘源减排.②经过策略寻优,反算得到了SO₂、NO_x、VOCs、一次PM_2.5的减排率分别为46%、20%、42%、60%的优化策略,该策略下的新增治污成本约4.69×108元;对比“十大措施”,优化策略提高了SO₂和一次PM_2.5的减排率,降低对O₃具有负贡献的NO_x减排率,满足空气质量目标的同时又尽可能地降低了治污成本,将效益-成本比提升至1.88.技术平台在济南市的初步成功应用,为济南市下一阶段的大气污染防治提供基于实证的科学依据;同时对其在我国城市逐步推广具有重要示范意义,可有效支撑大气污染防治综合科学决策制定.      

A TEST OF ALTERNATIVES FOR MEETING PUBLIC POTABLE WATER REQUIREMENTS1

ABSTRACT The relative economic costs of meeting projected public potable water demands through increasing the supply, controlling the demand, and increasing the capacity for interagency water transfers are explored. These alternatives and combinations are evaluated with the aid of a linear programming model in northeastern New Jersey, a major metropolitan region of over 4.5 million people, for the years 1975 to 2000. After more than 30 model tests it was found that a combination of increased interagency transfers and added water supplies was the least expensive solution.