面向突发事件的应急献血者聚类与分配方法研究

突发事件发生后,应急献血者呈爆发式增长、献血设施超负荷运作。本文提出一种应急献血者聚类与分配的优化方法可以有效地解决该问题。在该方法中,首先提出了应急献血者的分类规则,并采用Canopy与K-means相结合的算法对应急献血者进行聚类分组;然后,考虑献血者的心理因素,建立了最大化血液满足、均衡各献血设施的工作量以及最大化献血者效用的多目标分配优化模型;进一步,考虑应急献血者的时间偏好,构建了献血时间安排的多目标优化模型;通过使用优化算法求解模型得到应急献血者的分配方案;最后,通过一个算例分析验证了该方法的可行性以及有效性。     

Models for closed-loop supply chain with trade-ins

Three kinds of decision models for closed-loop supply chain (CLSC) with trade-ins are developed in this paper, including the centralized collection (Model C), the retailer collection (Model R), and the manufacturer collection (Model M). By analyzing these models, we argue that there are three types of optimal collection strategies, namely, no collection, partial collection, and full collection. We provide conditions under which one of these three collection strategies is optimal for different supply chain models. By comparing the impact of trade-ins on these different supply chain models, we find that only when the direct net value of a used product derived from the trade-ins for the whole CLSC system including the consumers is high enough can trade-in strategy be adopted to stimulate consumer demand and improve the manufacturer׳s and retailer׳s profit. Based on the life-cycle assessment method, we find that when the marginal effect of the product on environment in the continue-to-use phase is more significant than in other phases, trade-ins can promote the environmental performance of the CLSC system. Further, by comparing the optimal solutions for the different models, we find that one collection model may dominate the others in terms of the economic performance of the involved parties. Specifically, Model M dominates Model R in terms of the profits of the manufacturer and the profits of the whole supply chain; Model R dominates Model M in terms of retailer׳s profit; and Model R dominates all other models in terms of environmental performance.     

基于改进蚂蚁算法的拉动式供应链动态调度分析

分析了拉动式供应链调度动态性的产生根源,指出由于存在供应链协作成员之间复杂的协作与竞争关系,导致了供应链动态调度的特殊性;分析了供应链动态调度过程中的两个主要瓶颈.为了合理解决瓶颈问题,在优化供应链动态调度过程中引入蚁群觅食的寻优机理,并对其进行特定的算法设计及改进,提出供应链动态调度的蚂蚁寻优算法.仿真结果验证了算法可行有效.     

Supply Chain Scheduling: Distribution Systems

We study conflict and cooperation issues arising in a supply chain where a manufacturer makes products which are shipped to customers by a distributor. The manufacturer and the distributor each has an ideal schedule, determined by cost and capacity considerations. However, these two schedules are in general not well coordinated, which leads to poor overall performance. In this context, we study two practical problems. In both problems, the manufacturer focuses on minimizing unproductive time. The distributor minimizes customer cost measures in the first problem and minimizes inventory holding cost in the second problem. We first evaluate each party's conflict, which is the relative increase in cost that results from using the other party's optimal schedule. Since this conflict is often significant, we consider several practical scenarios about the level of cooperation between the manufacturer and the distributor. These scenarios define various scheduling problems for the manufacturer, the distributor, and the overall system. For each of these scheduling problems, we provide an algorithm. We demonstrate that the cost saving provided by cooperation between the decision makers is usually significant. Finally, we discuss the implications of our work for how manufacturers and distributors negotiate, coordinate, and implement their supply chain schedules in practice.     

Multi-objective permutation flow shop scheduling problem: Literature review,classification and current trends

The flow shop scheduling problem is finding a sequence given n jobs with same order at m machines according to certain performance measure(s). The job can be processed on at most one machine; meanwhile one machine can process at most one job. The most common objective for this problem is makespan. However, many real-world scheduling problems are multi-objective by nature. Over the years there have been several approaches used to deal with the multi-objective flow shop scheduling problems (MOFSP). Hence, in this study, we provide a brief literature review of the contributions to MOFSP and identify areas of opportunity for future research.     

A FRAMEWORK FOR MACHINE SCHEDULING PROBLEMS WITH CONTROLLABLE PROCESSING TIMES

This is a study of single and parallel machine scheduling problems with controllable processing time for each job. The processing time for job j depends on the position of the job in the schedule and is a function of the number of resource units allocated to its processing. Processing time functions and processing cost functions are allowed to be nonlinear. The scheduling problems considered here have important applications in industry and include many of the existing scheduling models as special cases. For the single machine problem, the objective is minimization of total compression costs plus a scheduling measure. The scheduling measures include makespan, total flow time, total differences in completion times, total differences in waiting times, and total earliness and tardiness with a common due date for all jobs. Except when the total earliness and tardiness measure is involved, each case the problem is solved efficiently. Under an assumption typically satisfied in just-in-time systems, the problem with total earliness and tardiness measure is also solved efficiently. Finally, for a large class of processing time functions; parallel machine problems with total flow time and total earliness and tardiness measures are solved efficiently. In each case we reduce the problem to a transportation problem.     

供应中断风险下OEM供应链弹性运作与提升策略

供应中断是OEM供应链中企业面临的主要风险。本文基于供应链弹性分析的角度，将OEM供应链弹性运作问题描述为多变量耦合控制模型，构建了可变结构的弹性控制系统，研究了在供应中断风险冲击下OEM供应链弹性交互影响机制。在此基础上，提出了一种有针对性的提升供应链弹性的深度学习机制，此算法比传统的BP神经网络更加能够提高供应链绩效，并结合案例进行验证。研究结果表明：当供应中断发生时，深度学习算法可有效提升OEM供应链弹性，最大程度减轻企业损失。     

A vendor–purchaser economic lot size problem with remanufacturing

In this paper, we study a closed-loop supply chain in which a single purchaser orders a particular product from a single vendor and sells it on the market. A certain fraction of used items return from the market back to the purchaser, who is responsible for collecting and returning them to the vendor. In addition to manufacturing new items, the vendor is able to remanufacture the returns into as-good-as-new items which are subsequently used to serve market demand. Our framework features the conventional joint economic lot size (JELS) model extended to include the return flow of the used items. In line with the assumptions of the JELS model, we assume a deterministic constant demand for the product. The fraction of used items returning from the market is assumed to depend on the purchaser’s collection effort. To stimulate the returns, the vendor may offer the purchaser a transfer payment per item returned. The questions addressed by this study pertain to the optimal centralised control of this closed-loop supply chain, to the individually optimal policies of its members, and to the coordination within this supply chain under a decentralised control. In particular, we show that the transfer payment alone cannot coordinate the supply chain under consideration and may even fail to do so when combined with a two-part tariff—which is otherwise known to coordinate the corresponding forward supply chain. Our numerical study, though, has revealed that the combined contract is capable of substantially reducing the coordination deficit. We also introduce a novel three-part tariff which is shown to enable supply chain coordination in combination with the transfer payment.     

努力弹性系数与成本同时扰动的闭环供应链协调应对研究

针对突发事件下销售努力弹性系数、回收努力弹性系数、制造成本和再制造成本同时扰动,研究了闭环供应链的制造(回收)策略、销售价格(回收价格)策略、销售努力(回收努力)策略与协调机制,给出了不同扰动条件下不同的制造(回收)调整策略、销售价格(回收价格)调整策略与销售努力(回收努力)调整策略,并设计了新的回馈与惩罚契约,使得闭环供应链能够在突发事件前后都能够实现协调应对,最后通过数值实例验证了文中结论的正确性。研究表明:闭环供应链受突发事件的影响很大,但通过对回馈与惩罚契约的调整及其相对应的制造(回收)策略、销售价格(回收价格)策略和销售努力(回收努力)策略的调整,可有效减少突发事件对闭环供应链利润的损失。     

Impacts of demand and supply factors on the capacity scheduling performance of logistics service supply chain with mass customisation service modes: an empirical study from China

This paper studies the influence of the demand–supply environment on the capacity scheduling performance of the logistics service supply chain. According to the key characteristics of the demand–supply environment, the cases of five Chinese companies were introduced and cross-analysed, then research hypotheses were developed. After receiving 154 valid questionnaires and testing our hypotheses, some key conclusions were obtained. From the aspect of demand, there is a positive correlation between the customised levels of demand and the scheduling cost of logistics service integrators but a negative correlation between the customised levels of demand and the scheduling flexibility; From the aspect of supply, a higher self-support ratio of logistics source and a higher sourcing integrity of logistics service integrators will lead to a higher scheduling cost and a lower scheduling flexibility; a whole-process performance evaluation is a moderator, which will positively improve the impact of the whole process scheduling performance.     

The Value of Production Schedule Integration in Supply Chains

This study explores the value of integrated production schedules for reducing the negative effects of schedule revisions in supply chains involving buyer and supplier firms. A stochastic cost model is developed to evaluate the total supply chain cost with integrated purchasing and scheduling policies. The model minimizes the costs associated with assembly rate adjustment, safety stock, and schedule changes for all supply chain members. Through experimentation, the paper examines the impact of several environmental factors on the value of schedule integration. This study finds that schedule integration can lead to overall cost savings in a supply chain, but some firms may have to absorb costs in excess of those they would incur with independent scheduling. Environments with high inventory holding costs and long supplier lead times may not find it beneficial to adopt an integrated schedule. Forecast effectiveness plays a critical role in realizing the benefits of schedule integration. The paper concludes with suggestions for future research.     

A multi-stage stochastic supply network design problem with financial decisions and risk management

In this paper, a multi-period supply chain network design problem is addressed. Several aspects of practical relevance are considered such as those related with the financial decisions that must be accounted for by a company managing a supply chain. The decisions to be made comprise the location of the facilities, the flow of commodities and the investments to make in alternative activities to those directly related with the supply chain design. Uncertainty is assumed for demand and interest rates, which is described by a set of scenarios. Therefore, for the entire planning horizon, a tree of scenarios is built. A target is set for the return on investment and the risk of falling below it is measured and accounted for. The service level is also measured and included in the objective function. The problem is formulated as a multi-stage stochastic mixed-integer linear programming problem. The goal is to maximize the total financial benefit. An alternative formulation which is based upon the paths in the scenario tree is also proposed. A methodology for measuring the value of the stochastic solution in this problem is discussed. Computational tests using randomly generated data are presented showing that the stochastic approach is worth considering in these types of problems.     

An Evaluation of Tour Scheduling Heuristics with Differences in Employee Productivity and Cost

This study focuses on the manpower tour scheduling problem using data from a lockbox system of a commercial bank. The lockbox system uses employees who differ in productivity, hourly cost, number of available working hours per week, and days-off constraints. These specific problem characteristics require a more general problem formulation and solution procedure for the manpower tour scheduling problem than addressed in previous research. Four heuristic methods for solving the problem (three developed here and a simple round-up procedure) are tested on a set of forty problems. The results of this study show the effort to develop sophisticated heuristic methods for this class of problems is well justified.     

MC模式下供应链动态调度的蚁群寻优分析

在对MC模式下供应链调度的基本运作特征描述及界定基础上,分析了调度过程中主导矛盾的缓解思路;通过将该思路引入动态调度的运作过程,分析了MC模式下的供应链动态调度机理.在调度求解过程中,引入蚁群觅食的寻优机理并对其进行特定的算法设计及改进,提出了供应链动态调度的蚂蚁寻优算法.算法特点为在运算过程中不仅能够反映该生产方式独特的运作特征要求,而且能够融入对主导矛盾的缓解思路.通过仿真,验证了算法的可行性.     

Keep Your Friends Close? Supply Chain Design and Disruption Risk

In this article, we evaluate the relationship between supply chain design decisions and supply chain disruption risk. We explore two supply chain design strategies: (i) the dispersion of supply chain partners to reduce supply chain disruption risk versus (ii) the co‐location of supply chain partners to reduce supply chain disruption risk. In addition, we assess supply chain disruption risk from three perspectives: the inbound material flow from the supplier (supply side), the internal production processes (internal), and the outbound material flow to the customer (customer side) as a disruption can occur at any of these locations. We measure disruption risk in terms of stoppages in flows, reductions in flow, close calls (disruptions that were prevented at the last minute), disruption duration (time until normal operation flow was restored), and the spread of disruptions all the way through the supply chain. We use seemingly unrelated regression (SUR) to analyze our data, finding that lead times, especially supply side lead times, are significantly associated with higher levels of supply chain disruption risk. We find co‐location with suppliers appears to have beneficial effects to the reduction of disruption duration, and, overall supply side factors have a higher impact when it comes to supply chain disruption risk than comparable customer side factors.     

Sharing Responsibility for Product Recovery Across the Supply Chain

Extended producer responsibility (EPR) programs typically hold the producer—a single actor defined by the regulator—responsible for the environmental impacts of end‐of‐life products. This is despite emphasis on the need to involve all actors in the supply chain in order to best achieve the aims of EPR. In this paper, we examine the economic and environmental implications of product recovery mandates and shared responsibility within a supply chain. We use a two‐echelon model consisting of a supplier and a manufacturer to determine the impacts of product collection and recycling mandates on the incentive to recycle and resulting profits in the integrated and decentralized supply chains. For the decentralized supply chain, we demonstrate how the sharing of responsibility for product recovery between the echelons can improve total supply chain profit and suggest a contract menu that can Pareto‐improve profits. To examine both the economic and environmental performance associated with responsibility sharing, we propose a social welfare construct that includes supply chain profit, consumer surplus, and the externalities associated with virgin material extraction, product consumption, and disposal of nonrecycled products. Using a numerical example, we discuss how responsibility sharing may or may not improve social welfare. The results of this paper are of value to firms either anticipating or subject to product recovery legislation, and to social planners that attempt to balance economic and environmental impacts and ensure fairness of such legislation.     

A Structural model for the impact of supply chain relationship traits on project performance in construction

The objectives of this study are to discover the supply chain relationship traits in construction and their impact on the project performance. Using factor analysis technique, the supply chain relationship traits were determined to be collaboration in the supply chain, support and commitment to the supply chain, and sharing the benefits and risks. A two-step SEM model was then established to test the hypothesised relationship between the supply chain relationship traits and the project performance. The findings indicated that the supply chain relationship traits have a significant positive impact on the project performance. This study contributes to the body of knowledge relating to the construction supply chain management. The findings may help the parties to identify the attributes that may improve the relationships among them and result in better project performance.     

Supply chain scheduling optimisation in mass customisation based on dynamic profit preference and application case study

Traditionally, the ‘postponement strategy’ is a better way to solve the contradiction between ‘scale production effect’ and ‘customised demand level’ in mass customisation (MC). In higher customisation situation, the conflict between the role of postponement and the higher level of customised demand must be outstanding. When MC operates in supply chain, the excellent flexible characters of the supply chain system will create better conditions to solve the conflict from a new perspective, but the operating combination of MC and the supply chain with uncertain characters will lead to various complicated contradictions and bottlenecks. In this article, we discuss the supply chain scheduling optimisation in MC based on dynamic profit preference to solve these contradictions and bottlenecks, establish a special optimisation model to implement the scheduling. We make a computational industrial case study to illustrate the method application and show the benefits of solving the key contradiction in MC by the supply chain scheduling.     

Vendor managed inventory in tramp shipping

This paper introduces a new problem to the OR community that combines traditional tramp shipping with a vendor managed inventory (VMI) service. Such a service may replace the more traditional contract of affreightment (COA) which for decades has been the standard agreement between a tramp shipping company and a charterer. We present a mathematical formulation describing the routing and scheduling problem faced by a tramp shipping company that offers a VMI service to its customers. The problem is formulated as an arc-flow model, and is then reformulated as a path-flow model which is solved using a hybrid approach that combines branch-and-price with a priori path-generation. To solve larger, and more realistic, instances we present a heuristic path-generation algorithm. Computational experiments show that the heuristic approach is much faster than the exact method, with insignificant reductions in solution quality. Further, we investigate the economic impact of introducing a VMI service, by comparing the results obtained with the new model with results obtained by solving the traditional routing and scheduling problem faced by tramp shipping companies using COA. The computational results show that it is possible to substantially increase supply chain profit and efficiency by replacing the traditional COAs with VMI services.     

Cross dock scheduling: Classification,literature review and research agenda

At cross docking terminals incoming deliveries of inbound trucks are unloaded, sorted, moved across the dock and finally loaded onto outbound trucks, which immediately leave the terminal towards their next destination in the distribution chain. Accordingly, a cross dock is a consolidation point in a distribution network, where multiple smaller shipments can be merged to full truck loads in order to realize economies in transportation. In this context, the truck scheduling problem, which decides on the succession of truck processing at the dock doors, is especially important to ensure a rapid turnover and on-time deliveries. Due to its high real-world significance, several truck scheduling procedures have been introduced during recent years, which all treat specific cross dock settings. In order to structure and promote scientific progress, this paper introduces a classification of deterministic truck scheduling. With the help of this classification, existing literature is reviewed and future research needs are identified. Moreover, we represent a yet unexplored class of truck scheduling problems which is highly relevant in real-world distribution networks.