Developing a fuzzy linear programming model for locating recovery facility in a closed loop supply chain

In this research a closed loop supply chain is designed which incorporates reverse logistics and forward logistic system simultaneously. In the design of reverse logistic system, recovery options are embedded in traditional supply chain for treating returned products. The recovery system includes collection centres, remanufacturing plants and disposal centres. Since the product return is supply driven, there is an uncertainty about it. In the proposed configuration for closed loop supply chain, the optimised configuration for supply chain in terms of locating recovery plants is developed. Accordingly, a fuzzy mixed integer linear programming model develops to deal with the uncertainty of returning products by customers. A general-purpose solver (LINGO 8.0) and a Meta heuristic approach (genetics algorithm) are implemented to solve the proposed model. The answers are compared by defining indexes and then the optimal answer, configuration and variables are identified. This solution will suggest a new design of supply chain network in which waste of materials is minimised and the new raw materials are necessary only when the used products may not be recovered by recovery options.     

An analytical platform for cumulative impact assessment based on multiple futures: the impact of petroleum drilling and forest harvesting on moose (Alces alces) and marten (Martes americana) habitats in northeastern British Columbia

The combined influence on the environment of all projects occurring in a single area is evaluated through cumulative impact assessments (CIA), which consider the consequences of multiple projects, each insignificant on its own, yet important when evaluated collectively. Traditionally, future human activities are included in CIA using an analytical platform, commonly based on complex models that supply precise predictions but with reduced accuracy. To compensate for the lack of accuracy in current CIA approaches, we propose a shift in the paradigm governing CIA. The paradigm shift involves a change in the focus of CIA investigations from the detailed analysis of one unlikely future to the identification of the patterns describing multiple potential future changes in the environment. To illustrate the approach, a set of 144 possible and equally likely futures were developed that aimed to identify the potential impacts of forest harvesting and petroleum drilling on the habitat suitability of moose and marten in northeast British Columbia, Canada. The evolution of two measures of habitat suitability (average habitat suitability index and surface of the stands with habitat suitability index >0.5) revealed that the human activities could induce cycles in the habitat dynamics of moose and marten. The planning period of 100 years was separated into three distinct periods following a sinusoidal pattern (i.e., increase - constant - decrease in the habitat suitability measures). The attributes that could induce significant changes in the assessment of environment are the choice of harvesting age and species.     

铁路危险货物办理站点优化配置方法研究

铁路危险货物运输办理站点的优化配置,涉及到需求分布、设置地点、区域规划、环保要求、业务功能以及与其他运输方式的分工、衔接等,是一个复杂的系统工程。分析了已有铁路危险货物办理站点整合优化模型的不足,首先从铁路部门角度综合考虑现有铁路危险货物办理站点的各方面条件,进行多准则决策评价,从运输需求者角度考虑运输方式多属性决策,进行铁路危险货物办理站点的综合效用评价,并基于投资成本、环境风险、运输效用和区域公平性等方面构建了铁路危险货物办理站点优化配置模型,为了有效解决多站点、多需求、多区域、多目标铁路危险货物办理站点优化配置模型因素复杂、规模大、层次多的问题,提出了运用大系统分解协调的多目标遗传算法求解模型的思路。     

基于GA优化算法的平遥县大气环境质量评价研究

本文以平遥县城及周边区域环境空气质量监测结果为依据,采用具有全局优化的遗传算法（GA）对平遥县及周边区域大气环境质量污染现状进行评价。用大气污染危害指数的普适公式和参数优化后的污染危害指数公式确定污染危害指数的取值范围与评价级别之间的对应关系,由此得出较符合平遥县及周边区域实际的评价结果,同时针对具体情况对此结果进行简单的分析。     

基于遗传算法的支持向量机预测有机物自燃点的研究

根据定量构效关系(QSPR)原理,研究自燃点(AIT)与其分子结构间的内在定量关系。以265种有机化合物作为样本集,随机选择238种作为训练集,27种作为测试集,用遗传算法(GA)进行变量选择,分别建立多元线性回归(MLR)模型和支持向量机(SVM)模型研究有机物的自燃点与其分子结构间的关系。通过分析,发现造成模型预测效果不佳的原因是试验数据本身存在问题。通过对2个模型的比较,结果为GA-SVM模型明显优于GA-MLR模型,说明自燃点与其分子结构间具有很强的非线性关系。     

基于在线检测信息的储罐底板腐蚀状态智能评价方法

为了解决利用声发射在线检测技术对储罐底板腐蚀状态进行评价时,主要依赖检测人员经验的问题,使该项技术能更好地推广和应用,利用储罐底板在线检测的声发射信息和外观检查信息,并根据相关标准及专家经验,确定与储罐底板腐蚀状态相关的表征因素。采用遗传算法(GA)改进贝叶斯网络(BN)搜索方法,建立基于GA的BN智能评价方法。针对声发射在线检测信息和外观检查信息,分别建立基于标准用声发射因素、基于声发射因素和综合考虑声发射因素和外观检查因素的基于在线检测信息的储罐底板腐蚀状态评价模型。通过对测试样本的评价,对比声发射检测专家评价结果,其中基于在线检测信息的储罐底板腐蚀状态评价模型的准确率为96%,该模型能够对储罐底板腐蚀状态进行可靠的智能评价。     

Kinetic parameter estimation for decomposition of organic peroxides by means of DSC measurements

The thermal stability of organic peroxides (cumene hydroperoxide 80 wt% and dicumyl peroxide) was studied by means of calorimetric measurement (DSC, TA Q1000) in an isotherm mode and a dynamic mode. Analysis of power profiles released in the isothermal mode was combined with the analysis of the decomposed compounds by a gas chromatograph/mass spectrometer (GC/MS) to determine the reaction mechanisms corresponding to each of the two reactions. In this work, a methodology for estimating kinetic parameters was based on the comparison of the power profile (dynamic mode) given by the model to that obtained experimentally by changing the parameters values. Parameter estimation is achieved using the mixed estimation method where a genetic algorithm is combined with a locally convergent method.     

灌区河道串联闸群防洪优化调度

针对河道串联闸群防洪优化调度的特点,详细推导了河道串联闸群防洪调度的洪水演算公式,明确了关键计算环节,建立了串联闸群防洪优化调度模型,应用水力学圣维南四点隐式差分法和遗传算法相结合对模型进行求解。采用VB6.0开发了人机交互的闸群防洪调度系统。通过实例计算,验证了河道串联闸群防洪优化调度方案的合理性,可为河道串联闸群防洪调度提供参考。     

基于Adam优化深度神经网络快速确定瓦斯抽采半径*

为解决煤矿瓦斯有效抽采半径难以快速准确确定的问题,采用基于Adam算法优化DNN（深度神经网络）方法来预测瓦斯抽采半径。查阅文献共收集已得到验证的970组数据集,每组数据选取煤层瓦斯初始渗透率、钻孔直径、抽采时间、地应力、煤层初始瓦斯压力作为预测模型的5个特征量,有效抽采半径作为目标输出值。接着预测模型进行不断学习和训练,最终训练得到1个最优的瓦斯有效抽采半径预测模型。利用训练好的最优预测模型结合Python语言开发出计算有效抽采半径的软件,并使用该软件在四季春煤矿和鹤煤六矿进行有效抽采半径预测的工程实例研究,验证该软件预测抽采半径的实用性和准确性。研究结果表明:通过使用开发的软件,可快速且较准确地计算出矿井瓦斯有效抽采半径,可为暂不具备现场测试条件的矿井抽采设计提供一定的参考依据。