An Improved Continuous Ant Algorithm for Optimization of Water Resources Problems

Ant colony optimization was initially proposed for discrete search spaces while in continuous domains, discretization of the search space has been widely practiced. Attempts for direct extension of ant algorithms to continuous decision spaces are rapidly growing. This paper briefly reviews the central idea and mathematical representation of a recently proposed algorithm for continuous domains followed by further improvements in order to make the algorithm adaptive and more efficient in locating near optimal solutions. Performance of the proposed improved algorithm has been tested on few well-known benchmark problems as well as a real-world water resource optimization problem. The comparison of the results obtained by the present method with those of other ant-based algorithms emphasizes the robustness of the proposed algorithm in searching the continuous space more efficiently as locating the closest, among other ant methods, to the global optimal solution.     

Water Supply Reservoir Operation by Combined Genetic Algorithm – Linear Programming (GA-LP) Approach

Multi-reservoir operation planning is a complex task involving many variables, objectives, and decisions. This paper applies a hybrid method using genetic algorithm (GA) and linear programming (LP) developed by the authors to determine operational decisions for a reservoir system over the optimization period. This method identifies part of the decision variables called cost reduction factors (CRFs) by GA and operational variables by LP. CRFs are introduced into the formulation to discourage reservoir depletion in the initial stages of the planning period. These factors are useful parameters that can be employed to determine operational decisions such as optimal releases and imports, in response to future inflow predictions. A part of the Roadford Water Supply System, UK, is used to demonstrate the performance of the GA-LP method in comparison to the RELAX algorithm. The proposed approach obtains comparable results ensuring non zero final storages in the larger reservoirs of the Roadford Hydrosystem. It shows potential for generating operating policy in the form of hegging rules without a priori imposition of their form.     

The Enhanced Honey-Bee Mating Optimization Algorithm for Water Resources Optimization

Evolutionary and meta-heuristic algorithms are widely used to solve water resources optimization problems. In this context, the honey bee mating optimization (HBMO) algorithm, inspired by the mating ritual of honey bees, is a reliable and efficient algorithm. The HBMO algorithm is modified in this work leading to the Enhanced HBMO (EHBMO) algorithm. The EHBMO is then applied to solve several unconstrained/constrained mathematical benchmark functions and a multi-reservoir problem. The performance of the EHBMO is compared with those of the elitist genetic algorithm (EGA) and the HBMO algorithm. The results show that the EHBMO achieves a better solution in a smaller number of functional evaluations and with less variance of results about global optima in comparison with the EGA and the HBMO algorithm.     

基于小生境遗传算法的区域水资源优化配置

水资源优化配置作为解决区域水资源短缺的重要手段,对保证整个区域国民经济的可持续发展起着重要的支撑作用。以水资源优化配置理论为基础,基于某市水资源现状,通过建立水资源分配模型,利用小生境遗传算法求解水资源在各部门的配置。     

遗传算法实现农村树状供水管网的优化设计

为改善农村树状供水管网的管径设计方案,应用数学建模和最优化理论,提出在确定管网布置方案的基础上,采用整数编码的遗传算法,建立管径组合方案优化模型。以经济性作为目标函数,并结合实例,编制相应计算程序,对某一农村供水管网进行优化设计,与传统设计方案进行对比。结果表明,该优化设计方案在经济性和水力特性都优于传统的设计方案。     

考虑相邻时段投切次数约束的动态无功优化启发式策略

在开关日动作次数约束基础上,考虑分接头挡位的相邻时段动作次数约束,建立了一种更加实用的动态无功优化新模型。按照“先投先切、后投后切”原则,将同一母线的多个电容器组等效为1个集中变量,并根据其中的电容器组个数来确定等效变量的动态约束值。由此,既满足了电容器的实际动态约束,又减小了模型的变量规模。在求解动态无功优化问题时,以混合智能算法为基础,提出处理动态约束的启发式调整策略,采用稀疏技术,有效提高了算法的效率。IEEE 14与IEEE 30节点系统和一个实际系统的仿真结果验证了所述模型的正确性和算法的有效性。     

基于PSO与DE混合算法的水资源优化配置

基于公平性原则构建水资源优化配置模型,针对模型的特点,将模型的可行解进行粒子化处理。利用基于粒子群(PSO)和差分进化(DE)的混合算法(PSODE)对模型进行求解。该算法通过双种群间的信息共享机制,大大降低了求解陷入局部最优的风险。此外,还采用了一种粒子变异机制进一步提高PSODE算法的性能,并通过漳河流域四大灌区水资源配置实例表明PSODE算法比PSO和DE算法收敛速度更快、准确度更高。     

蜜蜂进化型遗传算法在水库优化调度中的应用

提出了一种基于蜜蜂进化型遗传算法的水库优化调度问题的求解方法,并通过实例对蜜蜂进化型遗传算法和标准遗传算法的性能做了比较.结果表明,在进化代数相同的条件下,由于蜜蜂进化型遗传算法在配种选择算子上使用种群的最优个体作为蜂王,提高了种群收敛速度;再者,在代进化过程中引入一个随机种群,保持了群体的多样性,提高了算法的勘测能力.     

Multi-Reservoir Operation Planning Using Hybrid Genetic Algorithm and Linear Programming (GA-LP): An Alternative Stochastic Approach

Many models have been suggested to deal with the multi-reservoir operation planning stochastic optimization problem involving decisions on water releases from various reservoirs in different time periods of the year. A new approach using genetic algorithm (GA) and linear programming (LP) is proposed here to determine operational decisions for reservoirs of a hydro system throughout a planning period, with the possibility of considering a variety of equally likely hydrologic sequences representing inflows. This approach permits the evaluation of a reduced number of parameters by GA and operational variables by LP. The proposed algorithm is a stochastic approximation to the hydro system operation problem, with advantages such as simple implementation and the possibility of extracting useful parameters for future operational decisions. Implementation of the method is demonstrated through a small hypothetical hydrothermal system used in literature as an example for stochastic dual dynamic programming (SDDP) method of Pereira and Pinto (Pereira, M. V. F. and Pinto, L. M. V. G.: 1985, Water Res. Res. 21(6), 779–792). The proposed GA-LP approach performed equally well as compared to the SDDP method.     

基于试验遗传算法的水电站加劲压力埋管优化设计

水电站地下埋管的结构最优化设计是一个多维混合变量的非线性优化问题,采用常规优化方法求解有较大困难,为此提出基于试验优化设计思想的改进遗传算法———试验遗传算法。实例表明,由于该算法能自动调整计算精度,更好地保持种群多样性而易获得全局最优点,且计算简单、高效,对水利水电工程中常见的高维非线性优化问题适用性强,具有较高的推广应用价值。     

基于遗传算法的漫湾水电站厂内优化运行研究

运用MATLAB采用遗传算法对水电站厂内机组负荷分配情况进行模拟计算,在发电量满足调度要求并保证安全优质的情况下对机组负荷分配进行调整,优化机组运行使电站的耗流量减少;并对计算数据进行分析,研究峰谷负荷差对耗流量的影响。结果显示,峰谷负荷差对电站耗流量的影响可以做出定量的分析,该结论对于制定峰谷时差电价有一定指导意义,对于安排水电站优化运行,提高水电站运行效率有十分重要的现实意义。     

基于遗传算法的多目标问题求解方法

寻求非劣解集是多目标决策的基本手段。已有成熟的非劣解生成技术本质上都是以标量优化的手段通过多次计算得到非劣解集。目前遗传算法在多目标问题中的应用方法多数是根据决策偏好信息，先将多目标问题标量化处理为单目标问题后再以遗传算法求解，仍然没有脱离传统的多目标问题分步解决的方式。在没有偏好信息条件下直接使用遗传算法推求多目标问题的非劣解集的研究尚不多见。     

基于加速遗传算法的堆石坝施工优化

为实现水电站施工资源优化配置,提高水电站建设的经济效益,提出了堆石坝施工优化模型;模型中考虑了日上升高程约束和相邻区的高差约束,并用加速遗传算法实现了优化计算。对国内某一在建堆石坝的计算结果表明．该方法是可行的,对大坝建设期间的资源配置和强度计划制定有一定指导意义。     

混沌蚁群算法在水库优化调度中的应用

提出一种基于混沌优化算法和蚁群算法相结合的混合算法,在求解水库优化调度问题的方法。根据混沌变量的随机性和遍历性,利用混沌变量进行优化搜索,从而有效地克服了蚁群算法存在的效率低、易于演化停滞及陷入局部最优等问题。又利用蚁群算法信息素正反馈的优点,改善了混沌搜索的盲目性,提高了搜索的效率。通过实例计算,结果表明该算法具有效率高及较强的全局寻优能力。     

A New Optimization Approach for the Least-Cost Design of Water Distribution Networks: Improved Crow Search Algorithm

Due to large number of decision variables and several hydraulic constraints, optimal design of water distribution networks (WDNs) is considered as one of the most complex optimization problems. This paper introduces and applies a new optimization approach, improved crow search algorithm (ICSA), based on the improvement of original crow search algorithm (CSA) by adding an operator parameter. Both approaches (i.e., CSA and ICSA) were applied to two case studies (i.e., Two-Reservoir and Khorramshahr City networks) by linking the hydraulic simulator (e.g., EPANET 2.0). The proposed ICSA saved the total construction cost by 2.16% and 1.79% for the Two-Reservoir and Khorramshahr City networks compared to the original CSA based on optimal network design, respectively. Results revealed that the proposed ICSA provided outstanding design for the both WDNs compared to previous studies and original CSA.

     

水利工程方案优选的投影寻踪方法

为处理模糊定性评价指标和定量评价指标的一致化和无量纲化,较难确定的各指标权重、差异不显著的综合评价指标值以及受主观因素影响较大的优选结果等水利工程方案优选过程中的重要问题,研制了基于模糊优先关系矩阵 A 的水利工程方案优选投影寻踪新方法（FPRM－PP）。提出了 A 的最优模糊一致性判断矩阵、一致性指标函数和一致性指标临界值,研制了用加速遗传算法检验、修正 A 的一致性,并同时计算 A 各方案优度值的新算法。结果说明：FPRM－PP方法直观、实用,矩阵修正幅度较小,计算结果稳定、精度高。     

洋河二灌区渠道优化设计新方法研究与应用

为了替代计算量大、重复工作多的传统经验试算法,通过尝试采用免疫遗传算法(IGA)对梯形渠道横断面设计进行优化,并将该方法应用于河北省怀来县洋河二灌区渠道改造工程。结果表明,IGA计算量小,精度高,结果丰富,有效地解决了渠道断面设计中的优化问题,具有较高的应用价值。     

遗传模拟退火和小生境遗传算法在水库优化调度中的比较

根据溪洛渡水库的具体情况,建立了以发电量最大为目标的水库优化调度非线性数学模型,并利用遗传模拟退火算法(GSA)和小生境遗传算法(NGA)分别求解模型.结果表明,GSA和NGA的收敛速度和计算结果都明显优于基本遗传算法;且两者相比,GSA的收敛性更强,但计算时间较长.而在求解水库长系列优化调度问题时,各遗传算法占用机时太多,且收敛能力较差.     

遗传算法在水库(群)优化调度研究中的应用综述

介绍了遗传算法在水库(群)优化调度中的应用背景及算法的收敛性,讨论了水库(群)优化调度中遗传算法的基本应用步骤以及存在的问题,给出了算法的各种改进方法,并对遗传算法的应用前景进行了展望.     

基于改进遗传算法的生态友好型水库调度

以锦屏梯级水库为案例,从系统工程论的角度出发,将梯级水库作为物理系统,以年发电量为目标函数,建立了梯级水库调度优化模型。为减少水库调度对河道生态系统的影响,在鱼类栖息地模拟的研究基础上,引入目标物种的生态需水过程对调度模型进行动态约束,并采用改进的遗传算法进行求解。研究得到了满足目标鱼类生态需水条件下发电量最大的梯级水库调度策略,并对生态流量满足程度与工程效益损失之间的定量响应关系进行了研究,提出了折中方案选择的基本原则。