A scenario planning approach for propositioning rescue centers for urban waterlog disasters

An urban waterlog disaster can produce severe results, such as residents’ property loss, environmental damages and pollution, and even casualties. This paper presents a system specification for urban waterlog disasters according to the analysis of urban waterlog disaster risks. Then, a two-stage stochastic mixed-integer programming model is formulated. The model minimizes the total logistics cost, and risk-induced penalties. Moreover, a deterministic counterpart of the stochastic model is proposed to study the expected value of perfect information. The multi-attribute utility theory is used to build assessment functions that assess the utility of the rescue system and the degree contributed to disaster relief for each rescue center. Finally, a real example of rescue logistics is examined for the urban waterlog disasters in Pudong District of Shanghai, China. Using the proposed model, two main results can be obtained. First, the expected value of perfect information experiment reveals that an additional ¥45,005 logistics cost and an additional ¥2417 risk-induced penalties can be incurred due to the presence of uncertainty. Second, as the weight of risk-induced penalty increases from 0.1 to 0.9, the logistics cost is increased by 41.21%, which thus contributes to a decrease of risk-induced penalty by 97.44%. Some managerial implications are discussed based on the numerical studies.     

基于遗传算法的双区型仓库拣货路径优化研究

拣货作业成本是物流成本的重要组成部分。根据物流配送中心传统双区型仓库拣货路径问题的特点,建立了数学模型,并设计了相应的遗传算法来求解该问题。在算例中,通过与传统穿越策略、S形启发式算法和动态规划方法的比较,结果表明以遗传算法优化拣货路径问题,可以明显减少拣货路径的距离及拣货作业时间,具有良好的实用性。     

考虑交通拥堵的冷链物流城市配送的GVRP研究

针对目前研究冷链物流车辆路径问题多未考虑交通拥堵对运营成本的影响,将道路拥堵因素融入到冷链物流绿色车辆路径（Green Vehicle Routing Problem）优化数学模型中。兼顾经济成本和环境成本,在时变网络下综合考虑冷链物流中车辆管理成本、运输能耗成本、货损成本、制冷成本以及客户需求时间窗的惩罚成本,同时引入运输和制冷过程中产生的碳排放成本,统筹安排车辆路径,使得物流企业整体运营成本最低,更绿色环保。在此基础上根据模型特点设计改进蚁群算法进行求解,用实例对模型和算法进行仿真,验证该模型和方法可以有效地规避拥堵时段,降低配送成本,促进物流企业的节能减排,可以为物流企业冷链配送路径决策提供良好的参考依据。     

考虑逆向物流第三方配送的选址路径问题研究

针对电子商务退货的大量产生,提出一种送取一体化的配送方式,第三方物流和自建物流结合的逆向物流配送策略。选址和路径问题LRP（Location Routing Problem）成为了很多物流配送企业正在面对和急需解决的难题。为了降低配送方式成本以及提高客户满意度,利用改进的遗传算法,首先在自建物流成本中加入时间窗惩罚函数,偏远地区的配送采用第三方物流配送方式,建立送取货为一体的逆向物流选址路径模型;然后针对问题的复杂性设计一种改进的遗传算法对模型进行求解,采用时间分布思想初始化种群,引入局部搜索算法,设计自适应的改进遗传算法;最后采用实验进行数据分析,通过物流成本的降低、运行时间的减少、运行效率的提高等数据验证了模型的可行性以及算法的有效性。     

Reverse logistics network design with stochastic lead times

This work is concerned with the efficient design of a reverse logistics network using an extended version of models currently found in the literature. Those traditional, basic models are formulated as mixed integer linear programs (MILP-model) and determine which facilities to open that minimize the investment, processing, transportation, disposal and penalty costs while supply, demand and capacity constraints are satisfied. However, we show that they can be improved when they are combined with a queueing model because it enables to account for (1) some dynamic aspects like lead time and inventory positions, and (2) the higher degree of uncertainty inherent to reverse logistics. Since this extension introduces nonlinear relationships, the problem is defined as a mixed integer nonlinear program (MINLP-model). Due to this additional complexity, the MINLP-model is presented for a single product-single-level network. Several examples are solved with a genetic algorithm based on the technique of differential evolution.     

改进MOPSO在物流节点选址模型中的应用

为了降低物流系统的运营成本,提高物流系统的运作效率,构建了物流系统运营成本最小以及顾客时间满意度最大的多目标物流节点选址模型,并在模型求解过程中针对多目标粒子群算法的不足,从外部存档的更新、粒子学习样本的选择以及粒子的变异三个方面进行改进,将改进的多目标粒子群算法用于物流节点选址模型的求解。仿真结果表明,改进的算法相较于其他优化算法,具有较好的分布性和收敛性。     

A reverse logistics decisions conceptual framework

This research work proposes a reverse logistics decisions conceptual framework that offers flexibility and covers a wide variety of situations that may arise in the practical working environment. The methodology adopted in this paper is inspired by and taken from the various research papers published in the literature. The proposed framework considers seven important elements of the reverse logistics system. It is divided into three hierarchical levels (strategic, tactical, and operational). By carrying out experimentation with the proposed conceptual model, all three levels were tested in different industrial sectors during its development. Three real-world case studies are presented to test and to show the flexibility and applicability of the framework. The proposed conceptual framework will help practitioners in the field to structure their reverse logistics activities and also help academics in developing better decision models.     

Flexible decision modeling of reverse logistics system: A value adding MCDM approach for alternative selection

The most favorable reverse manufacturing alternative arriving to collection centers has always been a key strategic consideration of any product recovery system. The nature of these decisions usually is considered to be multidimensional, interdisciplinary, complex, and unstructured due to lack of certainty in environment and information regarding time, quantity and quality of returns, etc. Fuzzy decision methodology provides an alternative framework to handle these reverse logistics system (RLS) complexities and to determine the decision strategies for best alternative selection for reprocessing. Designing a decision-making model for the same requires quantitative and qualitative evaluation based on criteria such as cost/time, legislative factors, environmental impact, quality, market, etc. Performance must be considered on the basis of these criteria to determine a suitable reverse manufacturing option depending on the expert opinion in this domain. In this paper, we propose a multiple criteria decision-making (MCDM) model based on fuzzy-set theory. The proposed model can help in designing effective and efficient flexible return policy depending on the various criteria. Further, companies can use this analysis as a strategic decision-making tool to develop fresh reprocessing facilities or efficiently use the already exiting facility. Finally, an example has been illustrated to highlight the procedural implementation of the proposed model. Further, this paper also makes an attempt to bring fuzzy-based flexible MCDM and reverse logistics together as a well-suited group decision support tool for alternative selections.     

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.     

Autonomic resource provisioning for multilayer cloud applications with K-nearest neighbor resource scaling and priority-based resource allocation

Providing a pool of various resources and services to customers on the Internet in exchanging money has made cloud computing as one of the most popular technologies. Management of the provided resources and services at the lowest cost and maximum profit is a crucial issue for cloud providers. Thus, cloud providers proceed to auto-scale the computing resources according to the users' requests in order to minimize the operational costs. Therefore, the required time and costs to scale-up and down computing resources are considered as one of the major limits of scaling which has made this issue an important challenge in cloud computing. In this paper, a new approach is proposed based on MAPE-K loop to auto-scale the resources for multilayered cloud applications. K-nearest neighbor (K-NN) algorithm is used to analyze and label virtual machines and statistical methods are used to make scaling decision. In addition, a resource allocation algorithm is proposed to allocate requests on the resources. Results of the simulation revealed that the proposed approach results in operational costs reduction, as well as improving the resource utilization, response time, and profit.     

Management of lifecycle costs and benefits: Lessons from information systems practice

Assessing the economic feasibility of information systems (IS) projects and operations remains a challenge for most organizations. This research investigates lifecycle cost and benefit management practices and demonstrates that, overall, although organizations intend to improve their information technology (IT) management, they squander many opportunities to do so. There are inconsistencies in cost/benefit management practices. Most organizations that integrate operational benefits into investment analyses do not acknowledge operational costs. Planned project goals are seldom formulated in a verifiable or measurable way; there is little structured feedback on individual lifecycle activities, nor co-ordination of various activities. Thus, the attitude towards cost/benefit management appears primarily context-related and incident-driven. A further development of the system lifecycle-based approach is needed to improve IT cost/benefit management theory and practice, because a coherent set of methods is required to assess IT costs and benefits throughout the entire lifecycle.     

正态分布处理时间下的4PL多到多网络设计

在第四方物流(4PL)承担多个供需点对之间物流任务的情况下,针对处理时间的不确定性,研究考虑正态分布处理时间的4PL多到多网络设计问题。建立了以最小化总物流成本为目标,带有随机配送时间约束的4PL多到多网络设计机会约束规划模型。根据问题特点,设计差分进化算法进行求解,并对其进行改进。最后,通过对不同规模的问题进行仿真实验来证明模型的合理性及算法的有效性。     

Green logistic vehicle routing problem: Routing light delivery vehicles in urban areas using a neuro-fuzzy model

Today’s growth in the level of traffic in cities is leading to both congestion and environmental pollution (exhaust emissions and noise), as well as increased costs. Traffic congestion makes cities less pleasant places to live in, a particular problem being the negative impact on health as a result of increased exhaust emissions. In addition to these emissions, another major effect of transport which can lead to serious health problems is noise (EEA, 2013a, 2013b). There is a strong tendency in the world towards the development of “clean” motor vehicles that do not pollute the environment, that is, that do not emit harmful substances in their exhaust fumes and which create less noise without causing other types of pollution. The growth in the influence of transport on the environment has resulted in planners formulating procedures which take into account the effect of traffic on the quality of life in urban areas. This paper presents a model for the routing of light delivery vehicles by logistics operators. The model presented takes into account the fact that logistics operators have a limited number of environmentally friendly vehicles (EFV) available to them. When defining a route, EFV vehicles and environmentally unfriendly vehicles (EUV) are considered separately. For solving the problem of routing in the model, an adaptive neural network was used which was trained by a simulated annealing algorithm. An adaptive neural network was used for assessing the performance of the network branches. The input parameters of the neural network were the logistics operating costs and environmental parameters (exhaust emissions and noise) for the given vehicle route. Each of the input parameters of the neural network was thoroughly examined. The input parameters were broken down into elements which further describe the state of the environment, noise and logistics operating costs. After obtaining the performance of the network links for calculating the route for EFV and EUV vehicles a modified Clark–Wright algorithm was used. The proposed model was tested on a network which simulates the conditions in the very centre of Belgrade. All of the input parameters of the model were obtained on the basis of 40 automatic measuring stations for monitoring the air quality (SEA, 2012).     

A fuzzy-based customer clustering approach with hierarchical structure for logistics network optimization

Customer clustering is an essential step to reduce the complexity of large-scale logistics network optimization. By properly grouping those customers with similar characteristics, logistics operators are able to reduce operational costs and improve customer satisfaction levels. However, due to the heterogeneity and high-dimension of customers’ characteristics, the customer clustering problem has not been widely studied. This paper presents a fuzzy-based customer clustering algorithm with a hierarchical analysis structure to address this issue. Customers’ characteristics are represented using linguistic variables under major and minor criteria, and then, fuzzy integration method is used to map the sub-criteria into the higher hierarchical criteria based on the trapezoidal fuzzy numbers. A fuzzy clustering algorithm based on Axiomatic Fuzzy Set is developed to group the customers into multiple clusters. The clustering validity index is designed to evaluate the effectiveness of the proposed algorithm and find the optimal clustering solution. Results from a case study in Anshun, China reveal that the proposed approach outperforms the other three prevailing algorithms to resolve the customer clustering problem. The proposed approach also demonstrates its capability of capturing the similarity and distinguishing the difference among customers. The tentative clustered regions, determined by five decision makers in Anshun City, are used to evaluate the effectiveness of the proposed approach. The validation results indicate that the clustered results from the proposed method match the actual clustered regions from the real world well. The proposed algorithm can be readily implemented in practice to help the logistics operators reduce operational costs and improve customer satisfaction levels. In addition, the proposed algorithm is potential to apply in other research domains.     

A scatter search approach to the optimum disassembly sequence problem

One of the most difficult problems faced by OR researchers in the reverse logistics field consists in determining an efficient disassembly sequence for a product at its end of life. In this paper, a scatter search (SS) metaheuristic is presented aiming to deal with the optimum disassembly sequence problem for the case of complex products with sequence-dependent disassembly costs, and assuming that only one component can be released at each time. The algorithm was tested over a set of 48 products consisting of 25, 50, 75 and 100 right-angled parallelepiped components, connected by different kinds of joints. A feasible disassembly sequence, consisting on the reverse of the assembly sequence, is always usable. Comparing by using some statistical analysis the costs of the sequence proposed by the SS algorithm with those corresponding to the reverse order, efficiency of the metaheuristic is shown up.     

基于变分不等式的多商品物流网络优化设计

为优化设计多级多商品流的物流网络,按网络状态把物流网络划分为静态网络和动态网络,分析了静态网络的基础设施建设和动态网络的物流活动问题,构建了可描述不同网络阶段的运营成本和建设成本函数,并且考虑了运营过程带来的环境污染问题,构建了治理费用函数。基于以上函数,建立以供给能力为约束条件,以总成本最小为目标的网络设计和重新设计模型,然后将模型转换为变分不等式问题,证明了所设计模型与变分不等式等价。最后通过算例,运用修正投影算法对模型进行数值演算和验证,得到了最优成本下的设施建设方案和物流组织方案。     

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。     

Supply Chain Management by H-Infinity Control

In this paper, a H _infin control technique is proposed for the management of a supply chain (SC) model linearized about nominal operating conditions. The performance considered is a weighted H _infin norm comprising the inventory and the orders placed by each site, hence controlling the bullwhip effect together with local management costs. It is shown how the optimization of local costs at each site is related to the performance of the whole chain and a decentralized control methodology is proposed based on this relation.     

Novel multi-objective resource allocation and activity scheduling for fourth party logistics

In order to reduce logistic costs, the scheduling of logistic tasks and resources for fourth party logistics (4PL) is studied. Current scheduling models only consider costs and finish times of each logistic resource or task. Not generally considered are the joint cost and time between two adjacent activities for a resource to process and two sequential activities of a task for two different resources to process are ignored. Therefore, a multi-objective scheduling model aiming at minimizing total operation costs, finishing time and tardiness of all logistic tasks in a 4PL is proposed. Not only are the joint cost and time of logistic activities between two adjacent activities and two sequential activities included but the constraints of resource time windows and due date of tasks are also considered. An improved nondominated sorting genetic algorithm (NSGA-II) is presented to solve the model. The validity of the proposed model and algorithm are verified by a corresponding case study.     

An integrated framework for blockchain-enabled supply chain trust management towards smart manufacturing

With the development of a new generation of information technology, smart manufacturing has put forward higher requirements for supply chain. It is necessary to ensure the synchronization of the supply chain operation and maintain the reliability of the supply chain management, therefore the trust evaluation for the supply chain becomes extremely important. Traditional supply chain management has problems such as information flow is easy to be tampered with, logistics is difficult to trace, and capital flow is not true, which leads to increased opportunity costs due to the lack of trust among transaction entities in the supply chain. The emergence of blockchain technology provides an opportunity to improve the supply chain ecosystem. In this paper, an integrated framework for blockchain-enabled supply chain trust management towards smart manufacturing is proposed to explain how to enhance trust management with the help of blockchain from the perspectives of information flow, logistics, and capital flow. An optimized trust management model is designed for better entities evaluation in supply chain. A coal mine equipment manufacturing industry scenario is presented to illustrate the effectiveness of the proposed framework.