A genetic algorithm-based heuristic for the dynamic integrated forward/reverse logistics network for 3PLs

Today's competitive business environment has resulted in increasing cooperation among individual companies as members of a supply chain. Accordingly, third party logistics providers (3PLs) must operate supply chains for a number of different clients who want to improve their logistics operations for both forward and reverse flows. As a result of the dynamic environment in which these supply chains must operate, 3PLs must make a sequence of inter-related decisions over time. However, in the past, the design of distribution networks has been independently conducted with respect to forward and reverse flows. Thus, this paper presents a mixed integer nonlinear programming model for the design of a dynamic integrated distribution network to account for the integrated aspect of optimizing the forward and return network simultaneously. Since such network design problems belong to a class of NP hard problems, a genetic algorithm-based heuristic with associated numerical results is presented and tested in a set of problems by an exact algorithm. Finally, a solution of a network plan would help in the determination of various resource plans for capacities of material handling equipments and human resources.     

Supply chain modeling in uncertain environment with bi-objective approach

Supply chain is viewed as a large-scale system that consists of production and inventory units, organized in a serial structure. Uncertainty is the main attribute in managing the supply chains. Managing a supply chain (SC) is very difficult, since various sources of uncertainty and complex interrelationships among various entities exist in the SC. Uncertainty may result from customer’s demand variability or unreliability in external suppliers. In this paper we develop an inventory model for an assembly supply chain network (each unit has at most one immediate successor, but any number of immediate predecessors) which fuzzy demand for single product in one hand and fuzzy reliability of external suppliers in other hand affect on determination of inventory policy in SCM. External supplier’s reliability has determined using a fuzzy expert system. Also the performance of supply chain is assessed by two criteria including total cost and fill rate. To solve this bi-criteria model, hybridization of multi-objective particle swarm optimization and simulation optimization is considered. Results indicate the efficiency of proposed approach in performance measurement.     

A new network epsilon-based DEA model for supply chain performance evaluation

Supply chain performance evaluation problems are inherently complex problems with multilayered internal linking activities and multiple entities. Data Envelopment Analysis (DEA) has been used to evaluate the relative performance of organizational units called Decision Making Units (DMUs). However, the conventional DEA models cannot take into consideration the complex nature of supply chains with internal linking activities. Network DEA models using radial measures of efficiency are used for supply chain performance evaluation problems. However, these models are not suitable for problems where radial and non-radial inputs and outputs must be considered simultaneously. DEA models using Epsilon-Based Measures (EBMs) of efficiency are proposed for a simultaneous consideration of radial and non-radial inputs and outputs. We extend the EBM model and propose a new Network EBM (NEBM) model. The proposed NEBM model combines the radial and non-radial measures of efficiency into a unified framework for solving network DEA problems. A case study is presented to exhibit the efficacy of the procedures and to demonstrate the applicability of the proposed method to a supply chain performance evaluation problem in the semiconductor industry.     

RFID together with multi-agent systems to control global value chains

Nowadays, the cooperative intelligent transport systems are part of a largest system. Transportations are modal operations integrated in logistics and, logistics is the main process of the supply chain management. The supply chain strategic management as a simultaneous local and global value chain is a collaborative/cooperative organization of stakeholders, many times in co-opetition, to perform a service to the customers respecting the time, place, price and quality levels. The transportation, like other logistics operations must add value, which is achieved in this case through compression lead times and order fulfillments. The complex supplier's network and the distribution channels must be efficient and the integral visibility (monitoring and tracing) of supply chain is a significant source of competitive advantage. Nowadays, the competition is not discussed between companies but among supply chains. This paper aims to evidence the current and emerging manufacturing and logistics system challenges as a new field of opportunities for the automation and control systems research community. Furthermore, the paper forecasts the use of radio frequency identification (RFID) technologies integrated into an information and communication technologies (ICT) framework based on distributed artificial intelligence (DAI) supported by a multi-agent system (MAS), as the most value advantage of supply chain management (SCM) in a cooperative intelligent logistics systems. Logistical platforms (production or distribution) as nodes of added value of supplying and distribution networks are proposed as critical points of the visibility of the inventory, where these technological needs are more evident.     

Multi-behavior agent model for planning in supply chains: An application to the lumber industry

Recent economic and international threats to western industries have encouraged companies to increase their performance in all ways possible. Many look to deal quickly with disturbances, reduce inventory, and exchange information promptly throughout the supply chain. In other words they want to become more agile. To reach this objective it is critical for planning systems to present planning strategies adapted to the different contexts, to attain better performances. Due to consolidation, the development of integrated supply chains and the use of inter-organizational information systems have increased business interdependencies and in turn the need for increased collaboration to deal with disturbance in a synchronized way. Thus, agility and synchronization in supply chains are critical to maintain overall performance. In order to develop tools to increase the agility of the supply chain and to promote the collaborative management of such disturbances, agent-based technology takes advantage of the ability of agents to make autonomous decisions in a distributed network through the use of advanced collaboration mechanisms. Moreover, because of the highly instable and dynamic environment of today's supply chains, planning agents must handle multiple problem solving approaches. This paper proposes a Multi-behavior planning agent model using different planning strategies when decisions are supported by a distributed planning system. The implementation of this solution is realized through the FOR@C experimental agent-based platform, dedicated to supply chain planning for the lumber industry.     

基于供应商选择的大规模网络供应能力研究

在产品供不应求的市场环境下,为了最大限度地满足市场需求,核心企业需要对供应链中的供应商组合进行选择,实现整个供应链网络的最大供应能力。为了有效地解决组合方案规模庞大、计算困难的问题,采用了嵌套的混合遗传算法对此问题进行优化,提出了一种计算大规模网络最大流的新算法。算例结果显示,该方法能够正确选择供应商组合,并求解网络的最大供应能力。     

The physics of e-commerce supply chains

The Internet is rapidly improving our ability to support information flows across global supply chains. However, the business impact of these IT investments depends not just on the information flows supported by such systems, but also on other non-information related characteristics of the supply chain. It is the complex interplay among these characteristics that results in business performance, or lack thereof. In order to better understand the business impact of IT investments in the supply chain, we are motivated to examine the ‘physics’ of supply chain structures. By physics, we mean the performance patterns inherent in its informational and physical characteristics. Using the systems dynamics methodology, we model basic information and physical characteristics of supply chains and examine their impact on some common measures of performance. Experiments with the models suggest that, in addition to information delays, physical delays also have a major impact on the stability of supply chains, as well as on operating cost. Moreover, the tradeoff between chain stability and responsiveness appears to be nonlinear, suggesting that a small compromise in responsiveness may yield larger gains in stability. Multi-tier chains appear to be less ‘stiff’ in responding to demand fluctuations, implying that their information systems must be specifically designed to overcome this structural tendency. These results have managerial implications in terms of designing the information and physical structure of a supply chain as well as for its operation.     

考虑不同节点行为要素特征的供应链演化规律研究

为研究供应链的实际演化规律,以复杂网络理论中的多局域世界模型为原型,提出了一种包含局域性节点与全局性节点且反映多种供应链行为要素的供应链网络演化模型。该模型验证了在自然演化情况下,现实供应链网络均具有一定的幂律性;通过算例对比分析说明,该模型相较现有文献中的演化网络能更好地模拟现实的供应链网络。研究表明,在供应链的自然演化过程中,网络的连通性和传输效率不断增强,由于新节点企业多与较大规模的企业合作而忽略了其他企业,其节点间紧密程度降低;企业与供应链网络的紧密度逐步发展到一定的程度将趋于稳定,大规模企业的发展速度先增加后放缓,各规模节点发展速度在中后期保持稳定。     

An integrated supply chain network design problem for bidirectional flows

Coordination among supply chains has elicited considerable attention in both academia and industry. This paper investigates an integrated supply chain network design problem that involves the determination of the locations for distribution centers and the assignment of customers and suppliers to the corresponding distribution centers. The problem simultaneously involves the distribution of products from the manufacturer to the customers and the collection of components from the suppliers to the manufacturer via cross-docking at distribution centers. The co-location of different types of distribution centers and coordinated transportation are introduced to achieve cost savings. A Lagrangian relaxation-based algorithm is then developed. Extensive computational experiments show that the proposed algorithm has stable performance and outperforms CPLEX for large-scale problems. An industrial case study is considered and sensitivity analysis is conducted to explore managerial insights. Finally, conclusions are drawn, and future research directions are outlined.     

基于关系阵搜寻路线的车辆运输网络优化模型

从多个出发点出发,经过一定的交通运输网络到达另外多个到达地点,寻求最优运输方案是网络优化的一个基本问题。常规的线性规划方法只考虑供应约束与需求约束,没有考虑交叉路口通行能力、路段通行能力等约束,没有按照路线求最优解,已不适应实际工程要求。给出按照路线寻求最优运输分配方案的网络优化模型。另外,对于稍微复杂一些的有向有环运输网络,通常路线搜索方法比较复杂且不易理解。给出了基于关系矩阵搜索有向有环网络有效路线的方法,建立了具有供应约束、路口和路段通行能力约束、需求约束的相应模型。易于编程且具有便于一般工程技术人员容易理解的优点。该模型与算法适合于某些工程量巨大的大型施工项目。     

A scalable P2P platform for the knowledge grid

The knowledge grid needs to operate with a scalable platform to provide large-scale intelligent services. A key function of such a platform is to efficiently support various complex queries in a dynamic large-scale network environment. This paper proposes a platform to support index-based path queries by incorporating a semantic overlay with an underlying structured P2P network that provides object location and management services. Various distributed indexing structures can be dynamically formed by publishing, semantic objects as indexing nodes. Queries are forwarded along the chains of semantic object pointers to search for objects. We investigate the deployment of a scalable distributed trie index for broadcast queries on key strings, propose a decentralized load balancing method for solving the problem of uneven load distribution incurred by heterogeneity of loads and node capacities and by the distributed trie index, and give an approach for improving the availability of the semantic overlay and its trie index. Experiments demonstrate the scalability of the proposed platform.     

Aerospace Supply Chains as Evolutionary Networks of Activities: Innovation via Risk‐Sharing Partnerships

In the aerospace industry competitive advantage is searched through product innovation. This paper sets out to explore the effects that relationship development in the commercial aerospace supply chains have on innovation and competitive advantage. A perspective of supply chains as complex activity networks is used for data analysis based on in‐depth interviews in a global setting. Applying these concepts of supply chains as the interaction of multiple work activities assists in comprehending the forces of change. The processes of change are characterized by expansive learning processes of creating instruments for initializing, developing and sustaining these relationships. These processes take place in a terrain of complex power exercises. The long‐term effects are totally dependent on nurturing the relationships. The findings may be useful to practitioners in understanding how implementation of successful supply chain changes may come about. It promotes risk‐sharing partnerships as instruments for innovation. The paper provides evidence of changing relationships in commercial aerospace supply chains.     

基于神经网络的工业大系统辨识及稳态递阶优化方法

为了对工业大系统进行稳态递阶优化,必须首先获得系统的稳态模型.从神经网络的分析人手,给出了工业大系统稳态模型的动态辨识方法及基于神经网络模型的推导方法.为了提高算法的收敛速度,引入Lagrange函数解决大系统优化问题中的各种约束,并用Hopfield网络实现了大系统稳态递阶优化的网络算法,最后给出了某一大系统辨识及优化的仿真结果.     

Application of a Fuzzy Feasibility Bayesian Probabilistic Estimation of supply chain backorder aging,unfilled backorders,and customer wait time using stochastic simulation with Markov blankets

Because supply chains are complex systems prone to uncertainty, statistical analysis is a useful tool for capturing their dynamics. Using data on acquisition history and data from case study reports, we used regression analysis to predict backorder aging using National Item Identification Numbers (NIINs) as unique identifiers. More than 56,000 NIINs were identified and used in the analysis. Bayesian analysis was then used to further investigate the NIIN component variables. The results indicated that it is statistically feasible to predict whether an individual NIIN has the propensity to become a backordered item. This paper describes the structure of a Bayesian network from a real-world supply chain data set and then determines a posterior probability distribution for backorders using a stochastic simulation based on Markov blankets. Fuzzy clustering was used to produce a funnel diagram that demonstrates that the Acquisition Advice Code, Acquisition Method Suffix Code, Acquisition Method Code, and Controlled Inventory Item Code backorder performance metric of a trigger group dimension may change dramatically with variations in administrative lead time, production lead time, unit price, quantity ordered, and stock. Triggers must be updated regularly and smoothly to keep up with the changing state of the supply chain backorder trigger clusters of market sensitiveness, collaborative process integration, information drivers, and flexibility.     

A discussion of simultaneous engineering and the manufacturing supply chain, from an ergonomics perspective

This paper discusses some of the ergonomics issues involved in Simultaneous Engineering from the perspective of supply chains. To be competitive in future markets, manufacturing companies must make greater use of the expertise and knowledge that is available from outside the company. This paper discusses some of the ergonomics issues involved in Simultaneous Engineering from the perspective of supply chains. It outlines some of the generic attributes of supply chains, and discusses some concepts of federated control systems as applied to supply chains. The implications of these for information flows and the management of distributed knowledge are then discussed. Most of this knowledge is human knowledge; consequently, the structure of supply chain teams is then discussed. Finally, some of the support requirements for such teams are listed, making the link to current ergonomics knowledge. Relevance to industry

The paper discusses some of the deeper issues in the use and operation of supply chains for product introduction, looking particularly at the control and information-handling aspects from an ergonomics viewpoint. It also discusses the organisational aspects of operating such supply chains, discussing the infrastuctural issues of expertise, training, and job support necessary for efficient, effective control of these supply chains.     

Resilience in supply networks: Definition,dimensions, and levels

Oftentimes, seemingly robust systems fail, almost inexplicably, due to unforeseen events leading to disruption. Exploration and research of the mechanisms behind the failure of such systems have revealed that those capable of surviving are not robust, but resilient. This has spawned a stream of research on the resilience of different complex systems, from ecosystems, to the human body, to supply chains and communication networks. Supply networks are complex adaptive systems in which a subset of agents create flow and are required to deliver such flow to sink agents located at the other end of the network. Delivery of flow under pre-defined service conditions requires resilient design and operation protocols.In this article, a supply network formalism is introduced, and the concept and dimensions of resilience in supply networks, explored. Five core components of resilience are derived from reviewed definitions; two resilience dimensions, structure and control protocols, and two resilience levels, agent and network level, are characterized based on insights from articles in literature. Finally, emerging trends in resilience research as well as current research gaps are presented and future work directions outlined.     

网络业务的NS-2仿真实现

网络研究人员必须通过不同条件下对网络的测试来考察互联网协议的健壮性和稳定性。虚拟网络试验台(VINT)项目改进了网络仿真器(NS)和一些相关的软件,使研究人员能够在更为复杂的情况下评估网络协议。NS是一个理想的虚拟实验台,它可以进行各种网络协议仿真比较,并且提供了带有大量协议库的开放的仿真器。多协议网络模拟器可以为低成本的实验提供一个良好的环境,可用于完全不同的研究领域的一个通用模拟环境,可以为网络学术界提供相当大的便利。这些便利包括已有协议的行为验证,可用于开发新协议的丰富的构件平台,在一个受控环境下研究大规模协议交互的可能性,以及能够更方便地比较不同方法的结果。     

An agent-based approach for e-manufacturing and supply chain integration

A major problem facing manufacturing organisations is how to provide efficient and cost-effective responses to the unpredictable changes taking place in a global market. This problem is made difficult by the complexity of supply chain networks coupled with the complexity of individual manufacturing systems within supply chains. Current systems such as manufacturing execution systems (MES), supply chain management (SCM) systems and enterprise resource planning (ERP) systems do not provide adequate facilities for addressing this problem. This paper presents an approach that would enable manufacturing organisations to dynamically and cost-effectively integrate, optimise, configure, simulate, restructure and control not only their own manufacturing systems but also their supply networks, in a co-ordinated manner to cope with the dynamic changes occurring in a global market. This is realised by a synergy of two emerging manufacturing concepts: Agent-based agile manufacturing systems and e-manufacturing. The concept is to represent a complex manufacturing system and its supply network with an agent-based modelling and simulation architecture and to dynamically generate alternative scenarios with respect to planning, scheduling, configuration and restructure of both the manufacturing system and its supply network based on the coordinated interactions amongst agents.     

Supply chain redesign for resilience using simulation

Supply chains are facing numerous changes that are contributing to increasing their complexity and vulnerability to disturbances, therefore, to survive, supply chains must be resilient. The paper presents a supply chain simulation study for a real case concerned with the Portuguese automotive supply chain. The subset automotive supply chain involved in the case study is a three-echelon supply chain, composed by one automaker, two 1st-tier suppliers, two 2nd-tier suppliers, and one outsource entity. The purpose of the study is to evaluate alternative supply chain scenarios for improving supply chain resilience to a disturbance and understanding how mitigation strategies affect each supply chain entity performance. Two strategies widely used to mitigate disturbance negative effects on supply chains were considered and six scenarios were designed. The scenarios differ in terms of presence or absence of a disturbance in one hand and presence or absence of a mitigation strategy in other hand. To evaluate the scenarios designed, two performance measures were defined per supply chain entity, Lead Time Ratio and Total Cost.     

Random network models and sensitivity algorithms for the analysis of ordering time and inventory state in multi-stage supply chains

Supply chains in reality face a highly dynamic and uncertain environment, especially the uncertain end-customer demands and orders. Since the condition of product market changes frequently, the tasks of order management, product planning, and inventory management are complex and difficult. It is imperative for companies to develop new ways to manage the randomness and uncertainty in market demands. Based on the graphical evaluation and review technique, this paper provides a simple but integrated stochastic network mathematical model for supply chain ordering time distribution analysis. Then the ordering time analysis model is extended so that the analysis of inventory level distribution characteristics of supply chain members is allowed. Further, to investigate the effects of different end-customer demands on upstream orders and relative inventory levels, model-based sensitivity analysis algorithms for ordering fluctuations and inventory fluctuations are developed. A detailed numerical example is presented to illustrate the application of the proposed models to a multi-stage supply chain system, and the results of which shows the effectiveness and flexibility of the proposed stochastic network models and algorithms in order and inventory management.