简易的遗传算法及其在控制中应用

鉴于一般智能控制理论的教科书对于遗传算法的介绍过于深奥难懂,特写此文,通俗介绍遗传算法,并且提出自己简易的变异算法和交叉算法,以及应用遗传算法的编程思路,以便工程人员应用和供同行专家评鉴.     

烃的含氧衍生物自燃点的QSPR预测研究

应用定量构效关系（QSPR）方法对烃的含氧衍生物的自燃点（AIT）及其与分子结构间的内在定量关系进行了研究。选取国际电工委员会（IEC）数据库中的76种烃的含氧衍生物作为样本集,选择65 种作为训练集用于建立预测模型,11 种作为测试集。采用遗传算法（GA）对变量进行筛选,结合线性和非线性方法分别建立多元线性回归( MLR) 模型和支持向量机( SVM) 模型,理论预测得到了11种烃的含氧衍生物的自燃点,最后对所构建模型的性能及应用域进行了评价。结果表明,经GA筛选得出MATS2e、nCOH、Dv、BEHv2、nCHR、GATS1v、IDE、Du等8种特征分子描述符,GA-MLR和GA-SVM模型的理论预测值与实验值均较为相符且后者更优,两个预测模型均比较稳定,且具备较强的预测能力和泛化推广性能。     

基于分层遗传算法的土钉支护方案研究

土钉支护方案的选择,对土钉设计十分重要。现行的土钉支护设计一般由工程类比或设计经验确定,可能造成材料浪费和安全隐患。将分层遗传算法应用于土钉支护方案的优化中。工程实例计算证明,经分层遗传算法优化后,在满足安全系数的前提下,土钉支护方案造价有所降低,优化效果良好。     

基于遗传算法的建设工程风险决策多目标优化研究

在建设工程风险决策过程中,只考虑单个目标因素的决策并不能满足实际工程的要求。为了使决策更加科学、合理,在风险识别和风险评价的基础上,综合考虑包括风险管理成本在内的多个目标因素对决策结果的影响,建立了工程风险多目标决策优化模型,通过多目标遗传算法NSGA-Ⅱ,实现了工程风险决策方案的优化。最后,对优化结果的分析和评价,证明了所建立的模型在解决工程风险决策问题上的有效性和实用性。     

Managing inter-firm projects: A systematic review and directions for future research

Although the management of inter-firm projects is increasingly being researched in a wide range of academic fields (project management, alliances and networks, organization studies), the findings of these studies rarely cross theoretical boundaries. In the present study, a systematic literature review of 219 contributions from 26 years of academic research on managing inter-firm projects identifies 22 key management issues underlying its contributions. Based on a two-dimensional framework (project stage and analytical sphere), a structured and integrative synthesis of relevant studies is outlined. Based on these findings, future investigations are proposed to focus on dynamic, contextual and structural aspects of the management of inter-firm projects.     

Optimal planning of distributed generation from the DisCo and the DGO viewpoints considering the uncertainties in future demand and electricity price

Since electricity demand is increasing continuously, it is necessary to invest in expansion of distribution network capacity. From the asset management point of view, it is necessary to encourage the private sector to invest in distribution network. To do this, distribution network managers must provide important opportunities for private sector to profit from their investments. One of the options for private sector is to invest on distributed generations (DGs). In this regard, distribution company (DisCo) must sign power purchase agreement (PPA) with DG owners (DGOs). So, optimal siting, sizing and PPA rates from economic point of view are important challenges which are considered as the main contribution of this paper. The proposed methodology of this paper applies load and price uncertainties into the planning problem. The proposed scheme involves using non-dominated sorting genetic algorithms II (NSGA II), since it attains non-dominated solutions in which DisCo and the DGO can put their personal preferences into practice. To evaluate the effectiveness of the suggested method, the computer simulations are done on a 33-bus distribution network and the results are discussed.     

A simulation optimisation tool for planning of low-income housing projects

Construction of low-income housing projects is a recurring process and is associated with uncertainties that arise from the unavailability of resources. This paper presents a case study that discusses how computer simulation and optimisation are used to aid government agencies and/or contractors in planning of such projects. It illustrates the optimisation of project objectives, taking into consideration the interaction amongst involved resources. As such, total duration and the associated total costs, including direct and indirect costs, can be estimated and optimised. One Youth Habitation project that is executed in 6th of October City in Egypt is analysed in a step-by-step procedure to demonstrate the capability of proposed computer simulation and optimisation prototype (named LIHouse{_}Sim) in the modelling construction of low-income housing projects using bearing block walls with hollow core technique. The presented tool proves its practicality to contractors in estimating the time and costs of the recurring process of low-income housing construction, considering complex interdependencies between construction resources and the uncertainties associated with construction activities. The LIHouse{_}Sim prototype is used to perform a wide analysis for the alternative of the effective optimisation criteria in the bearing block walls/hollow core technique and for the genetic algorithm optimisation approach elements.     

给水管网耦合优化调度模型的建立及应用

引入节点水龄作为优化调度的约束条件,以EPANET 2.0作为管网水力平差计算和水质模拟工具,建立了一种多水源管网的耦合优化调度模型,并采用双重遗传算法对其进行求解.该模型简化了变量空间,加快了收敛速度,提高了求解效率.将此模型应用于实际管网,取得了较为明显的优化效果.     

基于投影寻踪的建筑施工现场安全综合评价

为了克服施工现场安全评价中存在的主观性强、不易处理高维数据的缺陷,提出了基于投影寻踪模型施工现场安全评价的新方法.该方法利用遗传算法实现了投影寻踪技术,将样本的多维评价指标值投影为一维投影数据,并据投影值大小确定各现场的安全程度.工程应用实例表明,该模型易于评价,具有很强的客观性、适用性和可操作性,为施工现场安全评价提供了新的技术工具.     

基于RAGA的投影寻踪分类模型在评标中的应用

运用投影寻踪分类评价模型（PPC）,把高维数据转换到低维子空间,同时用实码加速遗传算法（RAGA）来优化投影指标函数和模型参数,从而根据投影值的大小进行项目决策,并结合实例进行了验证。