逆向物流流量不确定闭环供应链鲁棒运作策略设计

考虑一类同时具有再分销、再制造和再利用的闭环供应链在逆向物流流量不确定环境下的运作问题.采用具有已知概率的离散情景描述逆向物流流量的不确定性,利用基于情景分析的鲁棒线性优化方法建立该闭环供应链的多目标运作模型.设计了一个数值算例,其结果验证了运作策略的鲁棒性.在该算例基础上,分析了逆向物流流量的大小对闭环供应链系统运作性能的影响.     

基于双向反馈信息的逆向物流网络优化方法

研究物流配送网络优化问题,提高物流配送网络运行效率.考虑到物流中存在退货问题,针对传统物流优化网络是基于单项路径传递构建的,没有考虑退货等现象造成的逆向路径负荷增加,一旦逆向物流网络路径中的密度过大,造成运输中心密度负荷过高,使负向密度不能反馈到调度算法中,导致物流配送网络运行效率过低的问题.提出了一种基于双向反馈信息的物流网络优化调度方法.通过建立物流逆向配送网络关系的数学模型,利用双向反馈信息加权算法进行网络配送优化计算,从而充分考虑逆向路径负荷的情况,提高网络运行效率.实验证明,改进方法提高物流配送网络运行效率,取得了物流优化的满意的效果.     

逆向物流流量不确定闭环供应链鲁棒运作策略设计

考虑一类同时具有再分销,再制造和再利用的闭环供应链在逆向物流流量不确定环境下的运作问题.采用具有已知概率的离散情景描述逆向物流流量的不确定性,利用基于情景分析的鲁棒线性优化方法建立该闭环供应链的多目标运作模型.设计了一个数值算例,其结果验证了运作策略的鲁棒性.在该算例基础上,分析了逆向物流流量的大小对闭环供应链系统运作性能的影响.

     

基于碳排放权交易与排队论的闭环物流网络设计

为了解决低碳经济环境下闭环物流网络设计问题,在碳排放权交易的约束下,以排队论计算逆向物流节点的存储量,考虑物流网络的运输成本、存储成本、建设成本、时间惩罚成本及碳交易成本,建立了以总成本最低为目标的闭环物流网络设计模型.以遗传算法为基础设计了求解算法,通过案例验证了物流网络设计模型和求解算法的可行性,就碳排放配额、交易价格以及时间惩罚对物流网络结构的影响进行了分析,表明现行的碳排放权交易环境基本不会改变企业物流网络结构.     

考虑客户聚类与产品回收的两级闭环物流网络选址-路径优化

针对目前不合理的废旧产品回收以及物流活动产生的碳排放污染，提出了一种考虑客户聚类与产品回收的两级闭环物流网络选址-路径优化模型。首先，结合实际物流网络的动态性假设客户需求量和回收率的不确定性特征，以最小运营成本和最小环境影响为目标建立选址-路径优化模型；其次，对多目标进化算法进行改进，提出了考虑客户聚类结果的两级物流设施选址-路径问题求解算法；最后，对该优化算法进行算法性能分析，并以重庆市某企业为例进行了模型和算法验证。结果表明，所建立的模型和算法能有效降低决策难度并提高物流系统的运作效率，所求出的优化方案能减少物流运作成本和降低物流运输过程对环境的影响。     

随机中断下第三方物流弹复性网络设计*

实际环境下第三方物流（3PL）网络会面临各种不确定的中断风险。为了使3PL系统能够安全、有效的运作,研究3PL弹复性网络设计问题模型和算法。建立带有弹复性约束的3PL网络设计优化模型,通过选择开设3PL物流中心和3PL仓库最小化总物流成本,同时使弹复性满足要求水平。根据问题模型的NP特性,设计和声搜索(HS)算法进行求解,并采用蒙特卡洛仿真方法估算网络的弹复性。最后,通过仿真实验来验证模型的合理性及HS算法的有效性,并分析弹复性对算法性能和网络设计结果的影响 。仿真实验结果表明HS算法能够对问题进行有效求解。     

基于集成定位-运输路线安排问题的废旧家电逆向回收物流网络优化

针对废旧家电逆向回收物流成本高、效益差而导致其回收率低的问题,提出一种应用离散微粒群智能算法优化废旧家电逆向回收物流网络模型的方法。在系统分析废旧家电逆向回收物流网络结构与要素基础上,构建基于集成定位-运输路线安排问题的废旧家电逆向回收物流网络优化模型,引入随机交换序与部分映射交叉(PMX)算子使离散微粒群优化(DPSO)算法具备良好的全局及局部搜索能力,来对该模型进行智能优化与求解。实例仿真结果表明,通过该优化模型及算法得到的全局最优解具有良好的收敛性和有效性;同时,能有效降低废旧家电逆向回收物流运作总成本。     

考虑蓄意攻击的第三方物流多周期可靠性网络设计

研究多周期环境下的第三方物流(3PL) 可靠性网络设计问题, 并考虑蓄意攻击中断. 建立多层的3PL 可靠性网络设计模型. 网络优化模型在满足可靠性约束条件下优化各周期的网络结构, 包括物流设施的开设和运输量的确定, 使网络总成本最小. 蓄意攻击模型优化各周期的攻击策略使网络服务水平最低. 根据问题模型的特点, 设计改进的两层分布估计算法, 上层分布估计算法求解多周期3PL 网络设计模型, 下层分布估计算法求解多周期攻击模型. 最后, 通过仿真实验表明了模型的合理性和算法的有效性.

     

基于遗传模拟退火算法的多层设施选址方法

逆向物流网络是逆向物流系统高效运作的基础和前提,而设施的选址定位是逆向物流网络设计的核心问题.为此,提出一个多层设施选址模型,旨在构建由回收点、回收中心和生产点相结合的最佳逆向物流回收网络.根据模型特点,提出基于遗传模拟退火算法的求解方法,个体采用二进制十进制混合编码;提出基于Metropolis准则的特定遗传进化操作;设计顾客对回收点、回收点对回收中心的两个子分配算法保证所有约束的满足性.最后通过仿真实验,得到满意的设施选址方案.可见,选址模型和算法是一种有效的设施选址方法,具有一定的应用前景.     

逆向物流多产品两阶段再生产网络鲁棒优化

考虑不同周期内逆向物流回收数量的不确定性和再生产设备的生产能力约束,将逆向物流回收数量、再生产成本和市场需求作为不确定参数,以成本最小为目标,建立了包含生产成本、设备运作成本、库存成本在内的多周期多产品两阶段逆向物流网络鲁棒优化模型。通过算例验证了模型的有效性。     

Sustainability of digital libraries: a conceptual model and a research framework

This paper aims to develop a conceptual model and a research framework for study of the economic, social and environmental sustainability of digital libraries. The major factors that are related to the economic, social and environmental sustainability of digital libraries have been identified. Relevant research in digital information systems and services in general, and digital libraries in particular, have been discussed to illustrate different issues and challenges associated with each of the three forms of sustainability. Based on the discussions of relevant research that have implications on sustainability of information systems and services, the paper proposes a conceptual model and a theoretical research framework for study of the sustainability of digital libraries. It shows that the sustainable business models to support digital libraries should also support equitable access supported by specific design and usability guidelines that facilitate easier, better and cheaper access; support the personal, institutional and social culture of users; and at the same time conform with the policy and regulatory frameworks of the respective regions, countries and institutions. It is also shown that measures taken to improve the economic and social sustainability should also support the environmental sustainability guidelines, i.e. reduce the overall environmental impact of digital libraries. It is argued that the various factors affecting the different sustainability issues of digital libraries need to be studied together to build digital libraries that are economically, socially and environmentally sustainable.     

Credibility-based fuzzy mathematical programming model for green logistics design under uncertainty

Measuring and controlling emissions across the logistics network is an important challenge for today’s firms according to increasing concern about the environmental impact of business activities. This paper proposes a bi-objective credibility-based fuzzy mathematical programming model for designing the strategic configuration of a green logistics network under uncertain conditions. The model aims to minimize the environmental impacts and the total costs of network establishment simultaneously for the sake of providing a sensible balance between them. A popular but credible environmental impact assessment index, i.e., CO₂ equivalent index is used to model the environmental impact across the concerned logistics network. Since transportation mode and production technology play important roles on the concerned objectives, the proposed model integrates their respective decisions with those of strategic network design ones. In addition, to solve the proposed bi-objective fuzzy optimization model, an interactive fuzzy solution approach based upon credibility measure is developed. An industrial case study is also provided to show the applicability of the proposed model as well as the usefulness of its solution method.     

Characterization and explanation of the sustainability of the European wood manufacturing industries: A quantitative approach

This paper has a twofold purpose. First, to characterize the sustainability of the European wood manufacturing industry. In this way, a ranking of the European countries analyzed in terms of sustainability is established. To undertake this task the sustainability of each country is defined by using several indicators of diverse nature (economic, environmental and social). These indicators are aggregated into a composite or synthetic index with the help of a binary goal programming model. In this way, a ranking according to the sustainability of the wood manufacturing industry in the European countries studied is obtained. The second step in the research consists of explaining the causes behind the level of sustainability of each country. This task is carried out by taking the composite indexes of sustainability as endogenous variables and a tentative set of economic, environmental and social variables as explanatory variables. The link between endogenous and exogenous variables is made with the help of econometric models.     

遗传算法在退货逆向物流网络设计中的应用

退货产生的逆向物流是很多企业长期面临的难点,并成为学术界和企业界广泛关注的热点.逆向物流网络设计是逆向物流管理的首要任务,也是一类NP完全问题.遗传算法作为组合优化设计的一种算法,可有效地提高解决这类NP完全问题的效率.     

Energetic sustainability of routing algorithms for energy-harvesting wireless sensor networks

A new class of wireless sensor networks that harvest power from the environment is emerging because of its intrinsic capability of providing unbounded lifetime. While a lot of research has been focused on energy-aware routing schemes tailored to battery-operated networks, the problem of optimal routing for energy harvesting wireless sensor networks (EH-WSNs) has never been explored. The objective of routing optimization in this context is not extending network lifetime, but maximizing the workload that can be autonomously sustained by the network.In this work we present a methodology for assessing the energy efficiency of routing algorithms for networks whose nodes drain power from the environment. We first introduce the energetic sustainability problem, then we define the maximum energetically sustainable workload (MESW) as the objective function to be used to drive the optimization of routing algorithms for EH-WSNs.We propose a methodology that makes use of graph algorithms and network simulations for evaluating the MESW starting from a network topology, a routing algorithm and a distribution of the environmental power available at each node. We present a tool flow implementing the proposed methodology and we show comparative results achieved on several routing algorithms.Experimental results highlight that routing strategies that do not take into account environmental power do not provide optimal results in terms of workload sustainability. Using optimal routing algorithms may lead to sizeable enhancements of the maximum sustainable workload. Moreover, optimality strongly depends on environmental power configurations. Since environmental power sources change over time, our results prompt for a new class of routing algorithms for EH-WSNs that are able to dynamically adapt to time-varying environmental conditions.     

考虑道路扩建的区域物流网络设计优化模型

通过对区域物流网络中边、点上费用、容量、流量等的分析,结合实际问题中对道路扩建和物流设施容量设计决策的需要,构建基于物流时间需求的区域物流网络设计数学模型。模型以最小化物流网络构建成本、初期运营成本和物流时间需求惩罚成本为目标,基于网络中物流量的特征给出了约束条件,分析模型的特点开发了改进的拉格朗日松弛算法并予以求解。计算机软件对模型和算法的仿真给出了物流网络构建中各项成本之间的关系,验证了模型和算法的有效性和实用性。     

TBL理论下3C产品可持续闭环物流网络模糊优化

针对3C产品更新换代快、回收量不确定、回收处理不当危害大的特点,采用TBL（三重底线法）理论,考虑最低成本、最小环境影响、最大社会效益,构建了不确定环境下3C产品可持续闭环物流网络模型。为求解该模型,将回收量看成三角模糊参数,利用模糊机会约束方法将模糊约束转化为等价的清晰条件;并通过定义目标隶属度对模型中的子优化目标进行模糊化,将原始优化问题转换为基于最大满意度的单目标优化问题。以某市3C产品为例,通过遗传算法求解该模型,对比验证了模型的有效性。     

基于改进粒子群的农田W SN路由优化方法

农田无线传感器网络（WSN）应用环境复杂,影响网络传输的因素包括环境变化、作物生长等。路由协议作为网络数据采集过程中的重要环节,其能耗优化是近年来农田WSN领域的研究热点。传统的能耗优化路由算法多数只针对静态网络环境,难以适用于动态变化的农田监测场景。为此,提出一种基于改进粒子群（PSO）的路由优化算法RD-PSO。将不同的路由传输路径抽象为粒子,根据农田网络能耗、剩余能量、网络传输跳数、链路质量等关键因子构建适应度函数,以提高路径寻优的环境适应性。同时,针对PSO路由随机初始化时迭代效率低的问题,采用反向探测方法确定网络节点的初始化拓扑位置,缩短初始位置与最优解的距离,从而提高算法的收敛速度。实验结果表明,相较ELMR、EEABR和MR-PSO路由算法,RD-PSO算法具有更快的收敛速度,在网络生命周期、能耗均衡效果以及平均传输跳数等方面性能较优,其能提高路由算法在农田动态场景中的适配性。     

A particle swarm approach for optimizing a multi-stage closed loop supply chain for the solar cell industry

In order to implement sustainable strategies in a supply chain, enterprises should provide highly favorable and effective solutions for reducing carbon dioxide emissions, which brings out the issues of designing and managing a closed-loop supply chain (CLSC). This paper studies an integrated CLSC network design problem with cost and environmental concerns in the solar energy industry from sustainability perspectives. A multi-objective closed-loop supply chain design (MCSCD) model has been proposed, in consideration of many practical characteristics including flow conservation at each production/recycling unit of forward/reverse logistics (FL/RL), capacity expansion, and recycled components. A deterministic multi-objective mixed integer linear programming (MILP) model capturing the tradeoffs between the total cost and total CO₂ emissions was developed to address the multistage CSLC design problem. Subsequently, a multi-objective PSO (MOPSO) algorithm with crowding distance-based nondominated sorting approach is developed to search the near-optimal solution of the MCSCD model. The computational study shows that the proposed MOPSO algorithm is suitable and effective for solving large-scale complicated CLSC structure than the conventional branch-and-bound optimization approach. Analysis results show that an enterprise needs to apply an adequate recycling strategy or energy saving technology to achieve a better economic effectiveness if the carbon emission regulation is applied. Consequently, the Pareto optimal solution obtained from MOPSO algorithm may give the superior suggestions of CLSC design, such as factory location options, capacity expansion, technology selection, purchasing, and order fulfillment decisions in practice.