A new controller architecture for high performance, robust, andfault-tolerant control

We propose a new feedback controller architecture. The distinguished feature of our new controller architecture is that it shows structurally how the controller design for performance and robustness may be done separately which has the potential to overcome the conflict between performance and robustness in the traditional feedback framework. The controller architecture includes two parts: one part for performance and the other part for robustness. The controller architecture works in such a way that the feedback control system can be solely controlled by the performance controller when there is no model uncertainties and external disturbances and the robustification controller can only be active when there are model uncertainties or external disturbances     

A supplier selection and order allocation problem with stochastic demands

We consider a system comprising a retailer and a set of candidate suppliers that operates within a finite planning horizon of multiple periods. The retailer replenishes its inventory from the suppliers and satisfies stochastic customer demands. At the beginning of each period, the retailer makes decisions on the replenishment quantity, supplier selection and order allocation among the selected suppliers. An optimisation problem is formulated to minimise the total expected system cost, which includes an outer level stochastic dynamic program for the optimal replenishment quantity and an inner level integer program for supplier selection and order allocation with a given replenishment quantity. For the inner level subproblem, we develop a polynomial algorithm to obtain optimal decisions. For the outer level subproblem, we propose an efficient heuristic for the system with integer-valued inventory, based on the structural properties of the system with real-valued inventory. We investigate the efficiency of the proposed solution approach, as well as the impact of parameters on the optimal replenishment decision with numerical experiments.     

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.     

Business–IT fit in e-procurement systems: evidence from high-technology firms in China

Abstract.  Because of the influence of globalization and updated information technologies (IT), firms in China face an urgent need to adopt e-procurement systems (EP) to deal with their daily procurement activities. However, implementing EP in China encounters various uncertainties from internal and external business environments. To address this issue, this research aims to examine the fit between business and the IT environment and to study its impact on system performance. The literature review allows the proposal of two internal business environmental uncertainties and two external business environmental uncertainties covering the perspectives of process, knowledge, partnership and environment. Based on a multiple-case study performed in four Chinese firms that supply various personal computer components to a Taiwanese original equipment manufacturer via an EP, it was found that the firms' external and internal uncertainty factors affected the performance of EP. In addition, an EP with a low level of integration – the EP type used most frequently in China – can only achieve great performance when the adopting firms faced a low uncertainty of environment, partnership and process, and had low levels of IT knowledge. It was also observed that lack of fit between the business environment and EP produced extra burdens and costs in the buyer–supplier relationship. This significantly reduced the system performance of the Chinese firms. Hence, the contribution of this research can be twofold. First, practitioners in China can use this framework to diagnose their environmental conditions and then choose the appropriate type of EP to implement. Second, researchers can build upon this model to further examine the impact of fit on EP performance and generalize the results.     

Supplier behavior modeling and winner determination using parallel MDP

Behavioral uncertainty of a supplier is a major challenge to a buyer operating in e-procurement setting. Modeling suppliers’ behavior from past transactions, estimation of possible future performance and integrating this knowledge with the winner determination process can bring a new dimension to procurement process automation. We propose a states-space model to capture the uncertainty involved in long-term supplier behavior. The states represent the performance level of a supplier. This behavioral aspect is then integrated with the winner determination process of a multi-attribute reverse auction for efficient supplier selection using parallel MDP. We also propose an implementation framework to collect the feedback on supplier, generate an aggregate performance score and integrate it with the winner determination process. The performance aggregation and winner determination with help of Markov decision process effectively uses the past performance information. In addition, it updates performance information in regular invervals and allevates the problem of maintaining a long history. We compare the MDP-based selection with that of performance score-based selection through a simulation experiment. It is observed that our scheme gives better buyer utility, selects best suppliers and fetches better quality product. The benefits realized through these attributes to the buyer increases the efficiency of the MDP-based selection process.     

To be or not to B2B: Evaluating managerial choices for e-procurement channel adoption

E-procurement systems are computer systems and communication networks through which firms buy and sell products. We identify two types of e-procurement systems: extranets and e-markets. Extranets connect the buyer and its suppliers with a closed network, while e-markets create open networks for buyer and supplier interactions. The differences between them lie in system implementation costs, marketplace benefits, and the extent of supplier competitive advantage that develops due to information sharing. In this article, we develop a new theoretical model to analyze the adoption of e-procurement systems from the buyer’s perspective, to explore the set of conditions under which the buyer will prefer to procure via an electronic market instead of using proprietary extranet connections. The primary finding is that a buyer will adopt an e-market approach when the supplier’s competitive advantage derived from access to strategic information is modest compared with the marketplace benefits less the channel costs. In addition, we find that the buyer is likely to have a bigger trading network with an e-market than with an extranet in order to capture the greatest available benefits. Overall, this study offers guidelines for managers to design and select e-procurement channels to fit different procurement needs.     

A two phase variable neighborhood search for the multi-product inventory routing problem

We address a multi-product inventory routing problem and propose a two-phase Variable Neighborhood Search (VNS) metaheuristic to solve it. In the first phase, VNS is used to solve a capacitated vehicle routing problem at each period to find an initial solution without taking into account the inventory. In the second phase, we iteratively improve the initial solution while minimizing both the transportation and inventory costs. For this, we propose two different algorithms, a Variable Neighborhood Descent and a Variable Neighborhood Search. We present an heuristic and a Linear Programming formulation, which are applied after each local search move, to determine the amount of products to collect from each supplier at each period. During the exploration, we use priority rules for suppliers and vehicles, based on the current delivery schedule over the planning horizon. Computational results show the efficiency of the proposed two-phase approach.     

Auction-Based Mechanisms for Electronic Procurement

Auction-based mechanisms are extremely relevant in modern day electronic procurement systems since they enable a promising way of automating negotiations with suppliers and achieve the ideal goals of procurement efficiency and cost minimization. This paper surveys recent research and current art in the area of auction-based mechanisms for e-procurement. The survey delineates different representative scenarios in e-procurement where auctions can be deployed and describes the conceptual and mathematical aspects of different categories of procurement auctions. We discuss three broad categories: 1) single-item auctions: auctions for procuring a single unit or multiple units of a single homogeneous type of item; 2) multi-item auctions: auctions for procuring a single unit or multiple units of multiple items; and 3) multiattribute auctions where the procurement decisions are based not only on costs but also on attributes, such as lead times, maintenance contracts, quality, etc. In our review, we present the mathematical formulations under each of the above categories, bring out the game theoretic and computational issues involved in solving the problems, and summarize the current art. We also present a significant case study of auction based e-procurement at General Motors.     

A hybrid integrated architecture for energy consumption prediction

Irresponsible and negligent use of natural resources in the last five decades has made it an important priority to adopt more intelligent ways of managing existing resources, especially the ones related to energy. The main objective of this paper is to explore the opportunities of integrating internal data already stored in Data Warehouses together with external Big Data to improve energy consumption predictions. This paper presents a study in which we propose an architecture that makes use of already stored energy data and external unstructured information to improve knowledge acquisition and allow managers to make better decisions. This external knowledge is represented by a torrent of information that, in many cases, is hidden across heterogeneous and unstructured data sources, which are recuperated by an Information Extraction system. Alternatively, it is present in social networks expressed as user opinions. Furthermore, our approach applies data mining techniques to exploit the already integrated data. Our approach has been applied to a real case study and shows promising results. The experiments carried out in this work are twofold: (i) using and comparing diverse Artificial Intelligence methods, and (ii) validating our approach with data sources integration.     

基于IEEE P1500芯核测试控制结构设计

讨论了IEEE P1500测试架构,详细分析并实现了IP核的测试环(Wrapper)结构,给出了一种支持该标准的芯片级测试控制结构。该结构能控制基于总线结构的TAM以及P1500 Wrapper,通过芯片级CTAP控制器,支持串行或并行测试访问,实现了核内测试以及核间互连测试。同时该结构只需5根额外测试管脚。     

线性电机伺服系统的自适应鲁棒控制

通过对一类音圈电机直驱式精密伺服系统运动控制问题的研究,在只考虑系统标称模型的情况下,采用分数阶形式的趋近律,得到了一种有限时间滑模控制算法;与此同时,当系统存在参数不确定和外界干扰的情况下,将有限时间滑模控制方法和自适应控制理论相结合,构造了一种自适应滑模控制律.另一方面,本文还考虑了系统具有输入饱和约束的情况,通过引入一个辅助系统,进而设计了一种自适应抗饱和控制律.而且,文中对闭环系统的稳定性进行了证明.最后,仿真和实验对所提出控制策略的有效性和伺服精度进行了对比、分析和验证.     

A mathematical model for order splitting in a multiple supplier single-item inventory system

In this paper we develop a mathematical model which considers multiple-supplier single-item inventory systems. The lead times of the suppliers and demand arrival rate are random variables. All shortages are backordered. Continuous review (s, Q) policy has been assumed. When the inventory level hits the reorder level, the total order is split among n suppliers. The problem is to determine the reorder level and order quantity for each supplier so that the expected total cost per time unit, including ordering cost, procurement cost, inventory holding cost and shortage cost is minimized. We also conduct extensive numerical experiments to show the advantages of our model compared to the relevant models in the literature. In addition, some managerial insights are observed.     

A framework for anonymous but accountable self-organizing communities

In this paper we propose a novel architecture and approach to provide accountability for Web communities that require a high-level of privacy. A two-layered privacy protection architecture is proposed, that supports (i) registration of participants and enforcement of community rules, called internal accountability, and (ii) rule-based interaction with real world organizations, called external accountability. Our security protocols build upon community-based trust and limit the exposure of private data on trusted third parties.The two-layered architecture protects the mappings between real users and their virtual identities, and among the virtual users, while guaranteeing internal and external accountability. We target Web communities that are dynamic and self-organizing, i.e. roles and contributions of participants may change over time. The proposed concepts and protocols are implemented in our SyllabNet project that supports anonymous course evaluations by university students.     

A collaborative food safety service agent architecture with alerts and trust

With the recent advances in Internet and mobile technologies, there are increasing demands for ubiquitous access to food safety information for service integration and gathering first hand information. However, due to disparate food trading information among different food suppliers throughout the food supply chain such as food importers, food wholesalers, food retailers, it is still difficult for citizens to use them effectively during their marketplace shopping. To overcome this problem, we propose a Collaborative Food Safety Agent System (CFSAS) based on a scalable, flexible, and intelligent Multi-Agent Information System (MAIS) architecture for proactive aids and trust-based decision support on food purchasing to citizens. We formulate our MAIS architecture for CFSAS further with agent clusters based on a case study of the Center for Food Safety (CFS) in Hong Kong. Agent clusters may comprise several types of agents to achieve the goals involved in the major processes of a food safety mechanism. We show how agents help citizens better plan, understand, and specify their preferences collaboratively with the CFSAS. We further illustrate how this can be implemented with Web service technologies to integrate disparate food information resources along the food supply chain.     

A self-adaptation scheme for workflow management in multi-agent systems

Business processes, operational environment, variability of resources and user needs may change from time to time. An effective workflow management software system must be able to accommodate these changes. The ability to dynamically adapt to changes is a key success factor for workflow management systems. Holonic multi-agent systems (HMS) provide a flexible and reconfigurable architecture to accommodate changes based on dynamic organization and collaboration of autonomous agents. Although HMS provides a potential architecture to accommodate changes, the dynamic organization formed in HMS poses a challenge in the development of a new software development methodology to dynamically compose the services and adapt to changes as needed. This motivates us to study and propose a methodology to design self-adaptive software systems based on the HMS architecture. In this paper, we formulate a workflow adaptation problem (WAP) and propose an interaction mechanism based on contract net protocol (CNP) to find a solution to WAP to compose the services based on HMS. The interaction mechanism relies on a service publication and discovery scheme to find a set of task agents and a set of actor agents to compose the required services in HMS. We propose a viable self-adaptation scheme to reconfigure the agents and the composed services based on cooperation of agents in HMS to accommodate the changes in workflow and capabilities of actors. We propose architecture for our design methodology and present an application scenario to illustrate our idea.     

Agent-based web service for the design of a dynamic coordination mechanism in supply networks

The theory of network coordination presents an effective approach to improve the business processes within supply networks. The automation of the negotiation process among buyers and suppliers has become an important policy in the transactional networks. This leads to assessing the roles of both quantifiable and non-quantifiable parameters in coordination mechanisms with the aim of achieving higher performance. Here, we develop an e-based supply chain multi-agent model for the design of mass-customized on-line services. The model addresses the bullwhip effect in multi-stage supply chain and also clarifies the evaluation of inventory policies in various supply and demand uncertainties. To illustrate the feasibility of the approach, we implement a prototype system and evaluate its performance by simulation using Colored Petri Nets (CPNs). The validation results reveal the model efficiency in providing a more realistic optimization process that takes the dynamic information flow in uncertainty environments into consideration.     

Distributed resource allocation of second‐order multiagent systems with exogenous disturbances

In this paper, we study the resource allocation problem of second‐order multiagent systems with exogenous disturbances, and the communication networks are weight‐balanced digraphs. Different from the well‐studied resource allocation problems, our problem involves the disturbed second‐order dynamics of agents. In order to achieve the optimal allocation, we propose a distributed algorithm based on gradient descent and internal model approach. Furthermore, we analyze the convergence of the algorithm by constructing a suitable Lyapunov function. Moreover, we prove that the agents in the network can achieve the exact optimal allocation even in the presence of external disturbances. Finally, we provide two examples to illustrate our result.     

Inventory models for imperfect production and inspection processes with various inspection options under one-time and continuous improvement investment

This study investigates both internal and external effects of defective production and delivery from imperfect production and inspection processes in a stable production and inventory system, and subsequent defective returns and dispositions. We first develop profit-maximizing imperfect-quality inventory models for various inspection options (sampling inspection, entire lot screening, and no inspection) under one-time improvement investment in production and inspection reliability. We then present the models under continuous improvement (CI) investments over multiple periods, which have not been explored before. In a CI environment, we further propose an inspection alternative of changing an inspection option from entire lot screening to no inspection and vice versa. We develop an algorithm for finding the optimal inspection policy yielding a superior profit, among inspection option change between entire lot screening and no inspection and those without option change. Based on the analytical models along with numerical and simulation analyses, we provide important managerial implications to practicing managers and future research directions.     

Reasoning about knowledge,belief and certainty in hierarchical multi-agent systems

Multi-agent systems (MAS) have received extensive studies in the last decade. However, little attention is paid to investigation on reasoning about logics in MAS with hierarchical structures. This paper proposes a complete quantified temporal KBC (knowledge, belief and certainty) logic and corresponding reasoning in hierarchical multi-agent systems (HMAS). The key point is that internal beliefs and certainty, and external belief and certainty are considered in our logic. The internal beliefs and certainty show every agent is autonomous, while the external belief and certainty indicate the mutual influence of mental attitudes between two different agents on different layers in HMAS. To interpret this logic, we propose four classes of corresponding quantified interpreted systems, and define first-order KBC axiomatisations over HMAS, which are sound and complete with respect to the corresponding semantical classes. Finally, we give a case study to show the advantages in terms of expressiveness of our logic.     

Distributed adaptive control and stability verification for linear multiagent systems with heterogeneous actuator dynamics and system uncertainties

The contribution of this paper is a control synthesis and stability verification framework for linear time-invariant multiagent systems with heterogeneous actuator dynamics and system uncertainties. In particular, we first propose a distributed adaptive control architecture in a leader-follower setting for this class of high-order multiagent systems. The proposed architecture uses a hedging method, which alters the ideal reference model dynamics of each agent in order to ensure correct adaptation in the presence of heterogeneous actuator dynamics of these agents. We then use Lyapunov stability theory and linear matrix inequalities to analyse the proposed architecture. This analysis reveals a stability condition, where evaluation of this condition with respect to a given graph topology allows stability verification of the controlled multiagent system. From a practical point of view, this condition also shows a fundamental tradeoff between heterogeneous agent actuation capabilities and unknown parameters in agent dynamics. Several illustrative numerical examples are also provided to demonstrate the efficacy of the proposed architecture.