Dynamic supply chain scheduling

Based on a combination of fundamental results of modern optimal program control theory and operations research, an original approach to supply chain scheduling is developed in order to answer the challenges of dynamics, uncertainty, and adaptivity. Both supply chain schedule generation and execution control are represented as an optimal program control problem in combination with mathematical programming and interpreted as a dynamic process of operations control within an adaptive framework. Hence, the problems and models of planning, scheduling, and adaptation can be consistently integrated on a unified mathematical axiomatic of modern control theory. In addition, operations control and flow control models are integrated and applicable for both discrete and continuous processes. The application of optimal control for supply chain scheduling becomes possible by formulating the scheduling model as a linear non-stationary finite-dimensional controlled differential system with the convex area of admissible control and a reconfigurable structure. For this model class, theorems of optimal control existence can be used regarding supply chain scheduling. The essential structural property of this model are the linear right parts of differential equations. This allows applying methods of discrete optimization for optimal control calculation. The calculation procedure is based on applying Pontryagin’s maximum principle and the resulting essential reduction of problem dimensionality that is under solution at each instant of time. The gained insights contribute to supply chain scheduling theory, providing advanced insights into dynamics of the whole supply chains (and not any dyadic relations in them) and transition from a partial “one-way” schedule optimization to the feedback loop-based dynamic and adaptive supply chain planning and scheduling.     

IT与供应链管理

随着市场竞争的加剧 ,供应链管理开始受到推崇。IT在促进供应链管理方面起着重要的作用。应用信息技术可以有效削弱供应链管理中的典型问题 -BW效应 ,提高供应链的运营水平。     

Poisoning the software supply chain

To the indiscriminate and opportunistic attacker, breaking into a software package's development and distribution site and waiting until unsuspecting users install it is more efficient than locating and hacking into users' systems individually. Starting in 2002 and continuing in to 2003, we've seen new emphasis on this type of attack. All the recent activity has showcased the trend that attacks against open-source software distribution sites are increasing. The author looks at how softwares distribution-both open source and proprietary-can invite attacks.     

Energy supply planning and supply chain optimization under uncertainty

In energy supply planning and supply chain design, the coupling between long-term planning decisions like capital investment and short-term operation decisions like dispatching present a challenge, waiting to be tackled by systems and control engineers. The coupling is further complicated by uncertainties, which may arise from several sources including the market, politics, and technology. This paper addresses the coupling in the context of energy supply planning and supply chain design. We first discuss a simple two-stage stochastic program formulation that addresses optimization of an energy supply chain in the presence of uncertainties. The two-stage formulation can handle problems in which all design decisions are made up front and operating parameters act as ‘recourse’ decisions that can be varied from one time period to next based on realized values of uncertain parameters. The design of a biodiesel production network in the Southeastern region of the United States is used as an illustrative example. The discussion then moves on to a more complex multi-stage, multi-scale stochastic decision problem in which periodic investment/policy decisions are made on a time scale orders of magnitude slower than that of operating decisions. The problem of energy capacity planning is introduced as an example. In the particular problem we examine, annual acquisition of energy generation capacities of various types are coupled with hourly energy production and dispatch decisions. The increasing role of renewable sources like wind and solar necessitates the use of a fine-grained time scale for accurate assessment of their values. Use of storage intended to overcome the limitations of intermittent sources puts further demand on the modeling and optimization. Numerical challenges that arise from the multi-scale nature and uncertainties are reviewed and some possible modeling and numerical solution approaches are discussed.     

The impact of supply contracts on supply chain product-flow management

One of the performance issues faced by the supply chain (SC) is the competitive production and delivery of products to all partners of the SC. The supply contract linking the Original Equipment Manufacturer (OEM) with its suppliers currently represents an important decision tool influencing the production and delivery of final products.     

基于Multi-Agent的供应链系统模型及其仿真

针对具有复杂自适应特征的供应链系统,设计了一个基于multi-agent的制造业供应链系统仿真模型.该模型分别从企业主体层和业务流程层构建供应链系统的agent模型,通过各独立ageIlt之间的来实现系统从接到客户订单到交付产品的整个过程.通过将任务分解并引入合同网模型来建立制造商与供应商之间的高效协商机制.通过在swarm平台上的系统仿真实验表明,该模型可较好的反映供应链内部的运行状况,并有良好的测试效果和稳定性.     

Semi-online two-level supply chain scheduling problems

We consider two-level supply chain scheduling problems where customers release jobs to a manufacturer that has to process the jobs and deliver them to the customers. Processed jobs are grouped into batches, which are delivered to the customers as single shipments. The objective is to minimize the total cost which is the sum of the total flow time and the total delivery cost. Such problems have been considered in the off-line environment where future jobs are known, and in the online environment where at any time there is no information about future jobs. It is known that the best possible competitive ratio for an online algorithm is 2. We consider the problem in the semi-online environment, assuming that a lower bound P for all processing times is available a priori, and present a semi-online algorithm with competitive ratio \(\frac{2D}{D+P}\) where D is the cost of a delivery. Also, for the special case where all processing times are equal, we prove that the algorithm is \(1.045\sqrt{\frac{2-u}{u}}\)-competitive, where u is the density of the instance.     

The supply chain trading agent competition

Supply chain management deals with the planning and coordination of bidding, production, sourcing and procurement activities associated with one or more products. It is central to today’s global economy, leading to trillions of dollars in annual transactions worldwide. With the emergence of electronic marketplaces, it is only natural to seek automated solutions that are capable of rapidly evaluating a large number of bidding, sourcing and procurement options. In this paper, we detail a game we have designed to promote the research and evaluation of such solutions under realistic conditions. The game requires agents to manage the assembly of PCs, while competing with one another both for customer orders and for key components. We discuss how the game captures the complexity, stochasticity and competitive nature inherent to supply chain environments. A Web-based multi-agent simulation platform developed for the game was implemented in 2003 and validated in the context of the first Supply Chain Management Trading Agent Competition (TAC-SCM). A total of 20 teams from around the world competed with one another. We review agent strategies developed by different teams and discuss the merits of competition-based research over more traditional research methodologies in this area.     

On supply chain cash flow risks

This study models the supply chain related cash flow risks for a business entity measured by the standard deviations of cash inflows, outflows, and netflows of each period in a planning horizon. The goal is to provide an insightful look on how common practices that intend to improve the Cash Conversion Cycle (CCC), e.g., offering early payment discounts, may contribute to cash flow risks. We show the benefits and recommend the best policy of using Asset-Backed Securities (ABS) to finance accounts receivable as a means to shorten the CCC and lower the cash inflow risk. It is particularly helpful to small vendors having tight cash reserves and high financing costs.     

Dynamic supply chain design with inventory

In this paper, we deal with a facility location problem where we build new facilities or close down already existing facilities at two different distribution levels over a given time horizon. In addition, we allow to carry over stock in warehouses between consecutive periods. Our model intends to minimize the total costs, including transportation and inventory holding costs for products as well as fixed and operating costs for facilities.     

基于区块链的RFID供应链安全协议

针对传统集中式数据库设计的射频识别(RFID)供应链系统安全认证协议中存在产品溯源困难、数据透明度低、数据易丢失和易被篡改的问题,结合分布式数据库的区块链优秀技术,提出一种健壮的超轻量双向认证R F ID安全协议U PBBC.将RFID系统和区块链技术有机融合在一起,结合去中心化数据库优势创建一个安全的、基于区块链的供应链应用系统.通过安全性分析,证明所提系统及协议在数据泄露、防篡改、密钥公开、重放攻击等方面是安全的.通过与现有协议进行对比,表明U PBBC具有更好的安全性,协议在存储、计算和通信成本方面比现有的方案均具有优势.     

A study of emergency management of supply chain under supply disruption

Emergency is an important factor resulting in supply disruption risk. How to deal with emergency in supply chain arouses managers’ and researchers’ attention in recent years. In order to improve the effect of supply disruption risk management under this situation, this paper builds the supply disruption Emergency Management Model of supply chain from the angle of risk management and discusses whether the decision-making mechanism of the case-based reasoning can bring the better effect for supply disruption by using computational experiment. The results mainly show that the mechanism of risk assessment, risk identification, risk control and risk evaluation based on the case-based reasoning can effectively deal with supply disruption risk, and bring more profit and better service level for the members of supply chain.     

Optimizing dynamic supply chain formation in supply mesh using CSET model

A new e-Service model called dynamic supply chain is characterized by their dynamic nature in easily being formed and disbanded with the seamless connectivity provided by e-Marketplace. The new term “supply mesh” was coined to represent this virtual community of companies in which dynamic supply chains, as per project (also known as make-to-order), are formed across different tiers of suppliers. In a supply mesh, a dynamic supply chain can be formed vertically, from the top to the bottom layers, mediating different companies for a project. Companies that are on the same level laterally are usually competitors, and the companies that are linked vertically as supply chains are trading partners. From a global view, the companies that are connected in the supply mesh can be viewed as individual entities that have self-interest. They may compete for survival as well as collaborate with each other for jobs. Given such complex relations the challenge is to find an optimal group of members for a dynamic supply chain in the supply mesh. A multi-agent model called the collaborative single machine earliness/tardiness (CSET) model was recently proposed for the optimal formation of make-to-order supply chains. This paper investigates the possibilities of applying CSET in a supply mesh, and the corresponding allocation schemes are experimentally studied in simulations. One scheme called Cost-driven principle leads to destructive competition while the other one namely Pareto-optimal evolves into a cooperative competition that tries to mutually benefit every participant. The results, based on samples from the U.S. textile industry, show that a cooperative competition scheme is superior in terms of optimal allocation, which obtains maximum satisfaction for all participants.     

Aligning RFID applications with supply chain strategies

Many large retailers decided to adopt RFID as their new supply chain technology, but RFID adoption by all industries did not spread as rapidly as initially expected. We believe that its benefits constituted the major barrier to its adoption, and argued that a major contributor to the delay has been its inappropriate implementation. Our study reports the result of six in-depth case studies, which, together with case content analysis of 88 reported RFID applications, provided us with a clear view of the RFID implementation landscape, suggesting that organizations often mindlessly adopted RFID applications that were misaligned with their supply chain strategies, leading to unsatisfactory benefits. Insights into how organizations should adopt RFID were developed from our results and were discussed.     

A review of supply chain complexity drivers

Studies on supply chain complexity mainly use the static and dynamic complexity distinction. While static complexity describes the structure of the supply chain, the number and the variety of its components and strengths of interactions between these; the dynamic complexity represents the uncertainty in the supply chain and involves the aspects of time and randomness. This distinction is also valid when classifying the drivers of supply chain complexity according to the way they are generated. Supply chain complexity drivers (e.g., number/variety of suppliers, number/variety of customers, number/variety of interactions, conflicting policies, demand amplification, differing/conflicting/non-synchronized decisions and actions, incompatible IT systems) play a significant and varying role in dealing with complexity of the different types of supply chains (e.g., food, chemical, electronics, automotive).     

Information supply chain optimization with bandwidth limitations

Workflow management systems allow for visibility, control, and automation of many business processes. Recently, nonbusiness domains have taken an interest in the management of workflows, and the optimal assignment and scheduling of workflow tasks to users across a network. This research aims at developing a rigorous mathematical programming formulation of the workflow optimization problem. The resulting formulation is nonlinear, but a linearized version is produced. Three heuristics are developed to find solutions efficiently. Computational experiments are presented and analyzed, comparing solutions to the original linearized formulation with the three heuristics.     

A global supply chain risk management framework: An application of text-mining to identify region-specific supply chain risks

Nowadays global supply chains enable companies to enhance competitive advantages, increase manufacturing flexibility and reduce costs through a broader selection of suppliers. Despite these benefits, however, insufficient understanding of uncertain regional differences and changes often increases risks in supply chain operations and even leads to a complete disruption of a supply chain. This paper addresses this issue by proposing a text-mining based global supply chain risk management framework involving two phases. First, the extant literature about global supply chain risks was collected and analyzed using a text-based approaches, including term frequency, correlation, and bi-gram analysis. The results of these analyses revealed whether the term-related content is important in the studied literature, and correlated topic model clustering further assisted in defining potential supply chain risk factors. A risk categorization (hierarchy) containing a total of seven global supply chain risk types and underlying risk factors was developed based on the results. In the second phase, utilizing these risk factors, sentiment analysis was conducted on online news articles, selected according to the specific type of risk, to recognize the pattern of risk variation. The risk hierarchy and sentiment analysis results can improve the understanding of regional global supply chain risks and provide guidance in supplier selection.