An emergency logistics distribution approach for quick response to urgent relief demand in disasters

Quick response to the urgent relief needs right after natural disasters through efficient emergency logistics distribution is vital to the alleviation of disaster impact in the affected areas, which remains challenging in the field of logistics and related study areas. This paper presents a hybrid fuzzy clustering-optimization approach to the operation of emergency logistics co-distribution responding to the urgent relief demands in the crucial rescue period. Based on a proposed three-layer emergency logistics co-distribution conceptual framework, the proposed methodology involves two recursive mechanisms: (1) disaster-affected area grouping, and (2) relief co-distribution. Numerical studies with a real large-scale earthquake disaster occurring in Taiwan are conducted, and the corresponding results indicate the applicability of the proposed method and its potential advantages. We hope that this study can not only make the proposed emergency logistics system available with more benefits to the development of emergency logistics systems for the urgent needs of disaster areas around the world but also stimulate more excellent researches concerning emergency logistics management.     

Models for relief routing: Equity, efficiency and efficacy

In humanitarian relief operations, vehicle routing and supply allocation decisions are critically important. Similar routing and allocation decisions are studied for commercial settings where efficiency, in terms of minimizing cost, is the primary objective. Humanitarian relief is complicated by the presence of multiple objectives beyond minimizing cost. Routing and allocation decisions should result in quick and sufficient distribution of relief supplies, with a focus on equitable service to all aid recipients. However, quantifying such goals can be challenging. In this paper, we define and formulate performance metrics in relief distribution. We focus on efficacy (i.e., the extent to which the goals of quick and sufficient distribution are met) and equity (i.e., the extent to which all recipients receive comparable service). We explore how efficiency, efficacy, and equity influence the structure of vehicle routes and the distribution of resources. We identify trends and routing principles for humanitarian relief based on the analytical properties of the resulting problems and a series of computational tests.     

Real-time relief distribution in the aftermath of disasters – A rolling horizon approach

This paper presents a rolling horizon-based framework for real-time relief distribution in the aftermath of disasters. This framework consists of two modules. One is a state estimation and prediction module, which predicts relief demands and delivery times. The other is a relief distribution module, which solves for optimal relief distribution flows. The goal is to minimize the total time to deliver relief goods to satisfy the demand, considering uncertain data and of the risk-averse attitude of the decision-maker. A numerical example based on the large-scale earthquake that occurred on September 21, 1999 in Taiwan is presented to demonstrate the system.     

An approximation approach to a trade-off among efficiency,efficacy, and balance for relief pre-positioning in disaster management

This work develops a multi-objective, two-stage stochastic, non-linear, and mixed-integer mathematical model for relief pre-positioning in disaster management. Improved imbalance and efficacy measures are incorporated into the model based on a new utility level of the delivered relief commodities. This model considers the usage possibility of a set of alternative routes for each of the applied transportation modes and consequently improves the network reliability. An integrated separable programming-augmented ε-constraint approach is proposed to address the problem. The best Pareto-optimal solution is selected by PROMETHEE-II. The theoretical improvements of the presented approach are validated by experiments and a real case study.     

Stochastic optimization for investment in facilities in emergency prevention

A coordinated approach is developed to integrate three preventive measures (i.e. building reinforcement, reinforcement of road networks, and facility location of relief supplies), with the objectives of minimizing budgets and risk-induced penalties. The Conditional Value-at-Risk is employed as a decision-making tool to evaluate diverse decisions of prevention based on the degree of risk aversion. Based on a real-world case of an earthquake, a series of scenarios were designed, and the applicability of the proposed model was studied. The coordinated approach for investing preventive measures is cost-efficient in helping reduce the impact of disaster on society.     

旅游轨道悬挂式单轨局部双线三方向立体疏解方案研究

长治太行山旅游轨道大峡谷经八泉峡至川底段采用悬挂式单轨制式,其中八泉峡景区为核心景区,客流量大,与其他景区线路需进行三方向立体疏解。结合长治市旅游规划整体布局,阐述长治太行山旅游轨道车流组织、系统制式及线路规划,为达到局部疏解的目的,研究"区间四线""车站疏解""区间疏解"3个线路局部方案,以及"外包疏解""环形疏解""平行疏解"3个车站疏解方案,经综合分析,推荐局部采用车站疏解,站内采用环形疏解的交通创意。疏解方案将有效、合理地解决三方向双线的交通矛盾问题,实现乘降便捷性与交通快捷性。     

Securing the Sustainability of Global Medical Nuclear Supply Chains Through Economic Cost Recovery,Risk Management,and Optimization

In this paper, we develop a new generalized network model for the optimization of the complex operations of medical nuclear supply chains in the case of the radioisotope molybdenum, with a focus on minimizing the total operational cost, the total waste cost, and the risk associated with this highly time-sensitive and perishable, but critical, product used in health-care diagnostics. Our model allows for the evaluation of transitioning the production and processing of the radioisotope from highly enriched uranium targets to low enriched uranium targets. A case study for North America demonstrates how our model and computational framework can be applied in practice.     

Bi-objective bilevel optimization of distribution center locations considering user equilibria

We propose a bi-objective, bilevel optimization model for the location of relief distribution centers (DCs) in humanitarian logistics. The upper-level decision-maker (an aid-providing organization) selects locations for capacitated DCs. On the lower level, beneficiaries choose a DC according to distance and amount of supply to be expected. This effects a user equilibrium on the lower decision level. Upper level objectives are to minimize total opening cost for the DCs and total uncovered demand. We develop an exact algorithm for determining the Pareto frontier of the problem, integrating the adaptive epsilon-constraint method, a branch-and-bound procedure, and the Frank–Wolfe procedure.     

A multi-objective approach to scheduling joint participation with variable space and time preferences and opportunities

Activity scheduling supports activity-based analysis in travel demand management and promotes a potentially popular traveler assistance service. A multi-objective approach is proposed to schedule joint participation of multiple individuals, in which the candidate space-time opportunities for joint participation are identified by a concept of time-varying network-based prisms, and optimal opportunities for joint participation are determined by the non-dominated sorting genetic algorithm-II (NSGA-II) with four objectives (i) minimizing cost for congestion charges, (ii) maximizing participation desirability of time-of-day, (iii) minimizing total travel distance and (iv) time in the trips of multiple individuals. A scenario of joint participation among four people is designed and implemented to demonstrate the feasibility of this approach. The results suggest that this approach has the ability to schedule activities within real situations.     

Expense preference behavior in public transit systems

This paper extends previous works that view transit systems as minimizing their after-subsidy costs. The paper uses the expense preference behavior model in economics and derives first-order conditions for the manager. From the first-order conditions, the paper formally shows that the decomposition of relative price inefficiency between management behavior and subsidies found in the work of Sakano et al. (1997) can be derived from a utility maximizing model, thus placing that decomposition within the shadow price literature. Extensions to the models to calculate expense preference are also presented. The results of the estimated models show that transit systems have expense preference for capital and not labor. This expense preference behavior increases total costs by about 15% and capital subsidies by about 20%.     

Demystifying Chinese overseas investment in infrastructure: Port development,the Belt and Road Initiative and regional development

China's outward investment has increased tremendously in recent years and it is currently a global leader in the construction of transportation infrastructure. While its signature ‘Belt and Road Initiative’ (BRI) is often portrayed as a threat by policy makers and media in the West, this article approaches the BRI from the perspective of Beijing. We review Chinese infrastructure investment and show that rather than a monolithic strategy aimed at world domination, the BRI is driven by a range of Chinese stakeholders situated at different scales whose motives vary from achieving strategic geopolitical advantage to profit-maximization. We focus on port investments to demonstrate that the BRI accelerated an ongoing trend of increasing Chinese investment in overseas ports that began in the early 2000s. We subsequently present mini-case studies of port projects Gwadar, Pakistan and Kuantan, Malaysia, which illustrate that large Central Government state-owned enterprises (SOEs) pursue strategic objectives while SOEs situated at the province and city levels are motivated by economic incentives. All Chinese investors embrace the ‘port-park-city’ model pioneered by Shenzhen, and we highlight its potential to foster regional development. We conclude that future research on Chinese infrastructure projects should be relational, multi-scalar and multi-sited.     

Dynamic relief-demand management for emergency logistics operations under large-scale disasters

This paper presents a dynamic relief-demand management model for emergency logistics operations under imperfect information conditions in large-scale natural disasters. The proposed methodology consists of three steps: (1) data fusion to forecast relief demand in multiple areas, (2) fuzzy clustering to classify affected area into groups, and (3) multi-criteria decision making to rank the order of priority of groups. The results of tests accounting for different experimental scenarios indicate that the overall forecast errors are lower than 10% inferring the proposed method’s capability of dynamic relief-demand forecasting and allocation with imperfect information to facilitate emergency logistics operations.     

车辆修理集中化布局的双层规划模型研究

在对车辆修理点布局问题分析的基础上,以规划期内修理点的改扩建费用、运营费用和运输费用之和最小为目标建立上层模型,以运输费用最小为目标建立下层模型,以此建立了车辆修理点布局的双层规划优化模型,并给出了相应的求解算法。模型具有较好的适用性和实用性,为铁路车辆修理点的进一步优化调整奠定了较好的理论基础。     

基于列生成的高速铁路车站作业计划调度调整方法研究

大型高速铁路车站到发线及列车进路的冲突是调度调整的重点,为了提高调整效率和效果,在将问题抽象为时空网络上多商品流的基础上,考虑技术作业要求、作业间隔时间、线路和进路运用规则等约束条件,以列车总晚点时间小、旅客便捷性好为目标,构建集到发线、咽喉进路和到发时刻为一体的车站作业调度调整0-1整数规划模型。针对调度调整的强实时性,设计基于列生成的求解算法,并以长春西站为例进行验证。结果表明,该方法可在较短时间内得到满意的车站作业计划调整方案。     

Railway projects prioritisation for investment: Application of goal programming

This research develops a weighted integer goal-programming model for prioritising railway projects for investment. The goal of the model is to prioritise the identified projects for investment while maximising the objectives and meeting the budget limit for capital investment. The model minimises the goal deviations of the objectives. The objectives of the model include quantitative and qualitative attributes. The model is applied to prioritise the new railway projects, which have a total cost of Euro 2 billion for capital investment, identified and analysed by Department of Transport, Ireland. Even though the objective is maximising all the attributes, the investment decision is subject to financial availability. The study recommends investment options at different capital investment levels when the decision is made on the basis of economic benefits, revenue or qualitative goal scores.     

Comparing strategies for addressing delivery shortages in stochastic demand settings

In logistics networks involving one supply point (depot) and several geographically dispersed demand points (e.g., retail stores), delivery shortages will result if the design of delivery routes ignores random period-to-period fluctuations in customer demands. Delivery shortages may be costly enough for the depot to seek strategies to prevent them. A requirement for rational comparison of strategies is quantifying their effects on total supply chain costs. Accurate distance prediction models are developed to help satisfy this prerequisite for the transportation cost element. These models are integrated into a comparison of strategies on the basis of how these strategies affect inventory and transportation. The focus of findings from the comparison involves identifying the information cost thresholds for accepting/rejecting a demand-responsive strategy. The study's implications for choosing a strategy are presented. ©     

Multi-objective decision support to enhance environmental sustainability in maritime shipping: A review and future directions

This paper aims to examine the potential of multi-objective optimization (MOO) as a decision support to improving sustainability in maritime shipping. We focus on environmental sustainability and the trade-offs involved with economic and operational objectives. Through a systematic approach, we review the literature on environmental sustainability, decision support and multi-objective optimization in maritime shipping. We identify the gaps and directions for future research. It is expected that the next generation of decision support systems for maritime transport will exploit the theoretical development in MOO to facilitate informed decision making in maritime supply chains considering environmental sustainability and the competing objectives.     

Optimizing inventory decisions in a multi-stage multi-customer supply chain

Most supply chain models focus on two-stage chains in which vendors supply material to one customer. In this paper, we formulate a three-stage supply chain model where a firm can supply many customers. We deal with three inventory coordination mechanisms between chain members and solve a cost minimization model for each. We show that some of the coordination mechanisms can result in a significantly lower total cost than matching production and delivery along the chain. We provide some insights into when the added complexity of the second and third coordination mechanisms lead to significant cost reductions.     

应急物流配送问题的蚁群聚类算法研究

提出了一种用于解决突发事件下,物流配送多目标优化问题的蚁群聚类优化算法。突发事件下的物流配送规划一般包含两方面内容,将救灾物资运往受灾地区和将灾区的伤员及时送至各医疗点。将多目标问题转化为单目标问题,结合蚁群的墓地构造行为特点,利用改进LF蚁群聚类模型,以节点需求未得到满足的不满意度最小和路由时间最短为优化目标,用LF蚁群聚类方法按约束条件进行聚类,最终确定车辆路由线路。     

Vehicle routing optimization with soft time windows in a fuzzy random environment

This paper is concerned with a vehicle routing problem with soft time windows (VRPSTW) in a fuzzy random environment. Two objectives are considered: (1) minimize the total travel cost and (2) maximize the average satisfaction level of all customers. After setting up the model for the VRPSTW in a fuzzy random environment, the fuzzy random expected value concept is used to deal with the constraints and its equivalent crisp model is derived. The global–local–neighbor particle swarm optimization with exchangeable particles (GLNPSO-ep) is employed to solve the equivalent crisp model. A case study is also presented to illustrate the effectiveness of the proposed approach.