Minimizing takeoff and landing risk in helicopter pickup and delivery operations

The problem of minimizing total helicopter passenger risk caused by takeoffs and landings is studied. There are passenger pickup and delivery demands to be satisfied at given points by flights starting and ending in the same heliport and visiting several points. For each point, the delivery demand is the number of passengers to be transported from the heliport to this point and the pickup demand is the number of different passengers to be transported from this point to the heliport. Each pickup and delivery demand must be satisfied in full by one flight. There are an upper bound on the number of flights and an upper bound on the helicopter passenger capacity. The objective function is a linear combination of the numbers of passengers involved in takeoffs and landings at visited points. A solution is characterized by the number of flights, sets of visited points and their sequences for all flights. Properties of optimal solutions are established. Several cases are proved NP-hard. A quadratic boolean programming formulation and two dynamic programming algorithms are suggested for the general case. Computer experiments demonstrated that they are able to solve real-life instances. Polynomial time algorithms are presented for special cases. Implementation of the suggested solutions into the real helicopter operations should decrease the number of fatalities.     

Sharing shipment quantity information in the supply chain

This paper evaluates the benefit of a strategy of sharing shipment information, where one stage in a supply chain shares shipment quantity information with its immediate downstream customers—a practice also known as advanced shipping notice. Under a periodic review inventory policy, one supply-chain member places an order on its supplier every period. However, due to supplier's imperfect service, the supplier cannot always exactly satisfy what the customer orders on time. In particular, shipment quantities arriving at the customer, after a given lead-time, may be less (possibly more) than what the customer expects—we define this phenomenon as shipment quantity uncertainty. Where shipment quantity information is not shared with customers, the only way to respond is through safety stock. However, if the supplier shares such information, i.e. customers are informed every period of the shipment quantity dispatched, the customer may have enough time to adapt and resolve this uncertainty by adjusting its future order decisions. Our results indicate that in most circumstances this strategy, enabled by information technologies, helps supply-chain members resolve shipment quantity uncertainty well. This study provides an approach to quantify the value of shared shipment information and to help supply-chain members evaluate the cost-benefit trade-off during information system construction. Numerical examples are provided to indicate the impact of demand/shipment parameters on strategy implementation. While previous studies mainly focus on the information receiver's perspective, we evaluate a more general three-tier linear supply chain model via simulation, studying how this strategy affects the whole supply chain: the information sender, the information receiver and the subsequent downstream tier.     

带时间窗装卸货问题的改进多策略分组编码遗传算法

通过研究求解PDPTW的分组编码遗传算法（GGA）及多策略分组编码遗传算法（MSGGA），改进了GGA中的交叉算子及MSGGA中的路径调整策略，提出了易位组合交叉算子、单车路径重排策略及需求对换策略。求解了400个客户点的标准算例集，其中4个算例lc2_4_3、lrc1_4_1、lrc2_4_2和lrc2_4_3的行驶总路程有所减少。     

基于遗传算法的三级逆向物流网络设计模型研究

建立初始回收点以方便客户、提高回收速度以及建立集中回收中心以负责产品的收回、分拣并统一运送到相应的生产商或分销商修理地点是一种节约、有效的多层次产品回收模式。本文在即存研究基础之上,加入了考虑初始点回收成本、回收产品中再销售品的收益和可再利用品的收益等变量,提出了能够优化连接客户、集中回收中心和生产商三级逆向物流网络数学模型,最后灵敏度分析表明遗传算法对于求解这类问题是一种有效的方法。     

A visual interactive approach to classical and mixed vehicle routing problems with backhauls

In this paper a new visual interactive approach for the classical vehicle routing problem with backhauls (VRPB) and its extensions is presented. The classical VRPB is the problem of designing minimum cost routes from a single depot to two type customers that are known as Backhaul (pickup) and Linehaul (delivery) customers where deliveries after pickups are not allowed. The mixed VRPB is an extension of the classical VRPB where deliveries after pickups are allowed.     

Integrating commercial and residential pickup and delivery networks: A case study

This paper presents a strategic analysis of the network design problem faced by pickup and delivery companies operating in metropolitan areas and serving two or more classes of customers. The focus is on a division that treats commercial and residential customers separately, a situation motivated by their respective geographic densities and the size and frequency of their demand. In constructing driver work areas, it is necessary to take into account expected demand, vehicle capacity, time on the road, and the aspect ratio of the individual territories. This leads to a capacitated clustering problem with side constraints that has been the subject of intense research over the last decade.     

Optimization and heuristic methods supporting distributed manufacturing

New optimization and heuristic methods are described to address supply chain management problems in distributed manufacturing settings. Specifically, integer programming formulations and heuristic methods are developed to design and evaluate optimal or near-optimal delivery plans for material movements between sites in a truckload trucking environment for the benefit of carriers, customers and professional drivers. The tools developed herein are appropriate for examining delivery needs between suppliers, manufacturers, distribution centres, and customer locations. They are equally applicable to more complex situations involving the return of packaging materials to the original shipment site, or even concurrent consideration of multiple business entities with various shipment profiles. Realistically sized case studies are provided to demonstrate the efficacy of the approaches using data supplied by J.B. Hunt Transport, Inc.     

Optimal Purchase and Transportation Cost Lot Sizing for a Single Item

A review of the literature indicates that the traditional approach for evaluating quantity discount offerings for purchased items has not adequately considered the effect that transportation costs may have on the optimal order quantity; despite the general fact that purchased materials must bear transportation charges. The transportation cost structure for less-than-truckload (LTL) shipments reflects sizable reductions in freight rates when the shipment size exceeds one of the nominal rate breakpoints. However, the shipper must also be aware of the opportunity to reduce total freight costs by artificially inflating the actual shipping weight to the next rate breakpoint, in order that a lower marginal tariff is achieved for the entire shipment. Such over-declared shipments result in an effective freight rate schedule that is characterized by constant fixed charge segments in addition to the nominal marginal rates. Over-declared shipments are economical when the shipment volume is less than the rate breakpoint, but greater than a cost indifference point between the two adjacent marginal rates. This paper presents a simple analytical procedure for finding the order quantity that minimizes total purchase costs which reflect both transportation economies and quantity discounts. After first solving for the series of indifference points that apply to a particular freight rate schedule, a total purchase cost expression is presented that properly accounts for the actual transportation cost structure. The optimal purchase order quantity will be one of the four following possibilities: (1) the valid economic order quantity (EOQ), QC; (2) a purchase price breakpoint in excess of QC; (3) a transportation rate breakpoint in excess of QC; and (4) a modified EOQ which provides an over-declared shipment in excess of QC. Finally, an algorithm which systematically explores these four possibilities is presented and illustrated with a numerical example.     

供需未匹配的多车场多车型多货品可拆分取送货车辆路径问题

取送货车辆路径问题在多点调拨系统普遍存在,属于NP-hard问题。该问题研究通常需考虑车场数、车型种类、货品种类、客户服务次数等诸多因素,已有文献多假设客户间供需已匹配、单车场、单车型、单货品和取送货需求一次性满足,优化目标多设置为总路径最短。而从企业运营实践来看,运输方案不仅要规划客户间访问路径,还需进行客户间供需匹配;运输成本不仅与运距有关,还涉及运输货品的重量和派车成本;运输网络中多车场、多车型和多货品更加常见,且客户需求量往往大于车辆装载能力。因此,本文首次尝试基于"运距×运量"的车辆路径成本和基于额定吨位的固定派车成本之和最小为优化目标,建立同时考虑多车场、多车型、多货品、客户间供需未匹配和需求可拆分的取送货车辆路径问题模型,并设计基于大规模邻域搜索的迭代局部搜索求解算法。该算法采用基于运输效率提升的贪婪思想来快速构建高质量初始可行解,并通过引入四种移除算子、两种修复算子和车场车型调整优化策略形成大规模可行搜索邻域以增强全局寻优能力。基于18个文献算例和6个企业实例的数值实验结果表明：1）本文提出的算法在求解质量和求解效率方面均优于相关文献中的算法;2）相对人工调拨方案,本文设计的方案能够帮助企业节约33%的运输成本和21%的车次。本研究不仅可拓展取送货车辆路径问题现有理论,而且可为企业实际运营提供决策支持。     

Integrated planning of inbound and outbound logistics with a Rich Vehicle Routing Problem with backhauls

This paper addresses the integration of the planning decisions concerning inbound logistics in an industrial setting (from the suppliers to the mill) and outbound logistics (from the mill to customers). The goal is to find the minimum cost routing plan, which includes the cost-effective outbound and inbound daily routes (OIRs), consisting of a sequence of deliveries of customer orders, pickup of a full truck-load at a supplier, and its delivery to the mill. This study distinguishes between three planning strategies: opportunistic backhauling planning (OBP), integrated inbound and outbound planning (IIOP) and decoupled planning (DIOP), the latter being the commonly used, particularly in the case of the wood-based panel industry under study. From the point of view of process integration, OBP can be considered as an intermediate stage from DIOP to IIOP. The problem is modelled as a Vehicle Routing Problem with Backhauls, enriched with case-specific rules for visiting the backhaul, split deliveries to customers and the use of a heterogeneous fleet. A new fix-and-optimise matheuristic is proposed for this problem, seeking to obtain good quality solutions within a reasonable computational time. The results from its application to the wood-based panel industry in Portugal show that IIOP can help to reduce total costs in about 2.7%, when compared with DIOP, due to better use of the delivery truck and a reduction of the number of dedicated inbound routes. Regarding OBP, fostering the use of OIRs does not necessarily lead to better routing plans than DIOP, as it depends upon a favourable geographical configuration of the set of customers to be visited in a day, specifically, the relative distance between a linehaul that can be visited last in a route, a neighboring backhaul, and a mill. The paper further provides valuable managerial insights on how the routing plan is impacted by the values of business-related model parameters which are set by the planner with some degree of uncertainty. Results suggest that increasing the maximum length of the route will likely have the largest impact in reducing transportation costs. Moreover, increasing the value of a reward paid for visiting a backhaul can foster the percentage of OIR in the optimal routing plan.     

Cooperative sales promotion with a point-sharing policy: Advantages and limitations

Consumption-point programs have been commonly implemented in retail industries in efforts to promote sales and improve customer loyalty. In Korea, many retailers from different industries use a point-sharing policy to augment the conventional consumption-point program of each retailer. In a multi-retailer coalition under such a cooperative sales promotion policy, by purchasing from one coalition retailer, customers earn points that they can redeem points at other retailers in the coalition. On one hand, the introduction of this policy gives customers great flexibility for redeeming earned points, which can increase the demand at all retailers who promote the policy. On the other hand, the additional product costs associated with the points created by one retailer may spill over and be partly borne by other retailers, possibly distorting the coalition members’ equilibrium decisions under decentralized control. Under the general assumptions about the demand functions, we developed a model consisting of two retailers with fixed retail prices and addressed the retailers’ equilibrium decisions under a pure point-sharing policy. The findings suggest that the policy resulted in a cost spillover phenomenon. Then, we revealed that a pure point-sharing policy may fail to maximize the total profit of the coalition. Moreover, we showed that a pure point-sharing policy does not dominate the individual point scheme, which may explain the reason that point sharing is useful but not ubiquitously used in the real world. Our numerical examples also illustrate the way a pure point-sharing policy influences retailers’ profits when retail prices are decision variables. To improve the overall profit under the point-sharing policy further, we propose a target rebate contract to coordinate a pair of retailers. This contract can maximize the total profit and arbitrarily split the profit between retailers.     

A Performance Metric and Goal‐Setting Procedure for Deadline‐Oriented Processes

A performance metric and goal‐setting procedure is defined for an order fulfillment operation. In this operation, order requests arrive continuously, and filled orders are shipped at a specific time each day. The metric links the continuous operation of order fulfillment to the scheduled shipment times. To prescribe goals against the metric, a performance model is developed that incorporates the motivational effect of a goal. Goal‐Setting Theory is used to establish the performance goal and to show how to match arriving orders to deadlines based on their arrival times and expected processing times. Monte Carlo simulation on data from a large distribution center is used to demonstrate that setting these two parameters in the light of motivational research yields quite different results than doing so with an intuitive method. Moreover, a motivational goal leads to better operational performance; that is, correctly setting up the metric causes more customers to receive their orders sooner.     

Online pickup and delivery problem with constrained capacity to minimize latency

The online pickup and delivery problem is motivated by the takeaway order delivery on crowdsourcing delivery platform, which is a newly emerged online to offline business model based on sharing economy. Considering the features of crowdsourcing delivery, an online pickup and delivery problem with constrained capacity is proposed, whose objective is to route a delivery man with constrained capacity to serve requests released over time so as to minimize the total latency. We consider online point-to-point requests with single pickup location where each request has to be picked up at the single pickup location and delivered to its destination, and each request become available at its release time, which is not known in advance. The lower bound of this problem for various capacities is proved. Two online algorithms WR and WI are presented, the competitive ratios on a half line and on general metric space are proved respectively. Further, a computational study is conducted to compare the performance of these two online algorithms on random instances of general metric space. The result shows algorithm WR performs better than WI in random cases but not in the worst case.

     

基于产品新鲜度要求的保鲜成本投资与数量集配策略联合决策研究

文章以提供生鲜产品运输配送服务的物流企业为研究对象,考虑生鲜产品质量腐蚀特性,应用随机更新理论建立基于下游零售商产品新鲜度水平要求的保鲜投资与物流集配联合决策随机模型。模型分析指出单位时间的运输成本、集配惩罚成本与保鲜投入成本随保鲜投资决策与物流集配决策变化的内在规律。数值分析指出保鲜投资、物流集配及其联合决策的有效性和产品、成本、需求环境等参数与这些环境参数同时变化对保鲜投资决策、集配决策与企业运营成本的影响。     

Pool‐Point Distribution of Zero‐Inventory Products

We study zero‐inventory production‐distribution systems under pool‐point delivery. The zero‐inventory production and distribution paradigm is supported in a variety of industries in which a product cannot be inventoried because of its short shelf life. The advantages of pool‐point (or hub‐and‐spoke) distribution, explored extensively in the literature, include the efficient use of transportation resources and effective day‐to‐day management of operations. The setting of our analysis is as follows: A production facility (plant) with a finite production rate distributes its single product, which cannot be inventoried, to several pool points. Each pool point may require multiple truckloads to satisfy its customers' demand. A third‐party logistics provider then transports the product to individual customers surrounding each pool point. The production rate can be increased up to a certain limit by incurring additional cost. The delivery of the product is done by identical trucks, each having limited capacity and non‐negligible traveling time between the plant and the pool points. Our objective is to coordinate the production and transportation operations so that the total cost of production and distribution is minimized, while respecting the product lifetime and the delivery capacity constraints. This study attempts to develop intuition into zero‐inventory production‐distribution systems under pool‐point delivery by considering several variants of the above setting. These include multiple trucks, a modifiable production rate, and alternative objectives. Using a combination of theoretical analysis and computational experiments, we gain insights into optimizing the total cost of a production‐delivery plan by understanding the trade‐off between production and transportation.     

带货物权重的车辆路径问题及遗传算法

考虑一个分销中心、多个零售商组成的分销网络系统中具有柔性车辆能力的带货物权重的车辆路径问题.并根据车辆的满载情况采用了不同的运输策略,即单点运输和多点运输方式.在多点运输方式下,与以往诸多研究不同的是,文章建立了一种基于货物权重的VRP模型——WVRP,即在安排车辆线路时每个零售商的货物需求量也作为一个因素考虑,尽可能使车辆优先供货需求量较大的零售商.最后,针对问题的性质,开发了一种基于划分的遗传算法PB-GA对问题进行求解,并与一般遗传算法及常用的启发式算法进行了分析比较.     

An Anticipatory Governance Approach to Carbon Nanotubes

Carbon nanotubes (CNTs) are novel materials with remarkable properties; possible beneficial applications include aircraft frames, hydrogen storage, environmental sensors, electrical transmission, and many more. At the same time, precise characterization of their potential toxicity remains elusive, in part because engineered nanostructures pose challenges to existing assays, predictive models, and dosimetry. While these obstacles are surmountable, their presence suggests that scientific uncertainty regarding the hazards of CNTs is likely to persist. Traditional U.S. policy approaches implicitly pose the question: “What level of evidence is necessary and sufficient to justify regulatory action?” In the case of CNTs, such a strategy of risk analysis is of limited immediate utility to both regulators essaying to carry out their mandates, and users of CNTs seeking to provide an appropriate level of protection to employees, customers, and other stakeholders. In contrast, the concept of anticipatory governance suggests an alternative research focus, that is: “Given the conflicted character of the data, how should relevant actors respond?” Adopting the latter theoretical framework, this article argues that currently available data support treating CNTs “as if” they are hazardous, while simultaneously highlighting some systemic uncertainties in many of the experiments carried out to date. Such a conclusion implies limiting exposure throughout product lifecycles, and also points to the possible applicability of various conceptual tools, such as life‐cycle and multicriteria decision analysis approaches, in choosing appropriate courses of action in the face of prolonged uncertainty.     

集装箱码头堆场取箱时间窗优化研究

码头堆场是供装卸船舶存放集装箱的场所,同时也是向货主交接集装箱的地方.由于取箱车辆到达时间的不确定性,码头运营方需要在堆场进行大量的翻箱作业,消耗大量的劳动成本.首先对码头取箱时间窗优化机制进行了说明,构建了码头方补助金函数与车辆方的成本函数,获得了车辆方取箱的到达率函数,进而得到了码头方的翻箱次数公式.然后,描述了集...     

Storage constrained vendor managed inventory models with unequal shipment frequencies

We consider a supply chain where a vendor manages its multiple retailers' stocks under a vendor managed inventory (VMI) contract that specifies upper stock limits at the retailers' premises and overstock costs for exceeding those limits. We formulate a mixed integer nonlinear program that minimizes total supply chain costs and allows unequal shipment frequencies to the retailers. We develop an algorithm to solve its relaxed version which provides a lower bound cost solution. We propose a cost efficient heuristic procedure to generate delivery schedules to the retailers. We conduct a sensitivity analysis to provide insights on the performance of the proposed heuristic. Results show that our heuristic finds optimal or near optimal solutions, and it proposes substantial savings compared to the total supply-chain cost in the cases where there is no VMI and where there is VMI but with equal shipment frequencies to retailers.     

Hedging strategic flexibility in the distribution optimization problem

Motivated by the increasing prevalence of flexibility hedging in corporate-level risk management programs, this paper focuses on the treatment of hedging operational risks in the coordinated replenishment and shipment for distribution systems. The forward option pricing model with the generalized autoregressive conditional heteroskedasticity (GARCH) model for stochastic demand forecasting is adopted for constructing inventory volume flexibility. We therefore propose a hedge-based coordinated inventory replenishment and shipment (HCIRS) methodology for flexibly making inventory hedging and optimal routing assignment decisions as well as coordinating replenishment and shipment policies. The HCIRS methodology provides insight into strategic flexibility adopted for a real-life inventory–distribution problem faced by one of the major East Asia food supply networks and turns out to be very efficient. The proposed HCIRS methodology has provided evidence of better results than the traditional operational techniques for the presented case in this paper.