Corporate dashboards for integrated business and engineering decisions in oil refineries: An agent-based approach

It is generally very challenging for an oil refinery to make integrated decisions encompassing multiple functions based on a traditional Decision Support System (DSS), given the complexity and interactions of various decisions. To overcome this limitation, we propose an integrated DSS framework by combining both business and engineering systems with a dashboard. The dashboard serves as a human-computer interface and allows a decision maker to adjust decision variables and exchange information with the DSS. The proposed framework provides a two-stage decision making mechanism based on optimization and agent-based models. Under the proposed DSS, the decision maker decides on the values of a subset of decision variables. These values, or the first-stage decision, are forwarded through the dashboard to the DSS. For the given set of first-stage decision variables, a multi-objective robust optimization problem, based on an integrated business and engineering simulation model, is solved to obtain the values for a set of second-stage decision variables. The two-stage decision making process iterates until a convergence is achieved. A simple oil refinery case study with an example dashboard demonstrates the applicability of the integrated DSS.     

A cognitive approach for agent-based personalized recommendation

There is an increasing need for various e-service, e-commerce and e-business sites to provide personalized recommendations to on-line customers. This paper proposes a new type of personalized recommendation agents called fuzzy cognitive agents. Fuzzy cognitive agents are designed to give personalized suggestions based on the user’s current personal preferences, other user’s common preferences, and expert’s domain knowledge. Fuzzy cognitive agents are able to represent knowledge via extended fuzzy cognitive maps, to learn users’ preferences from most recent cases and to help customers make inferences and decisions through numeric computation instead of symbolic and logic deduction. A case study is included to illustrate how personalized recommendations are made by fuzzy cognitive agents in e-commerce sites. The case study demonstrates that the fuzzy cognitive agent is both flexible and effective in supporting e-commerce applications.     

A distributed agent-based approach for simulation-based optimization

Structural design and optimization in engineering are increasingly addressing non-standard optimization problems (NSPs). These problems are characterized by a complex topology of the optimization space with respect to nonlinearity, multimodality, discontinuity, etc. By that, NSP can only be solved by means of computer simulations. In addition, the corresponding numerical approaches applied often tend to be noisy. Typical examples for NSP occur in robust optimization, where the solution has to be robust with respect to implementation errors, production tolerances or uncertain environmental conditions. However, a generally applicable strategy for solving such problem categories always equally efficiently is not yet available.To improve the situation, a distributed agent-based optimization approach for solving NSPs is introduced in this paper. The elaborated approach consists of a network of cooperating but also competing strategy agents that wrap various strategies, especially optimization methods (e.g. SQP, DE, ES, PSO, etc.) using different search characteristics. In particular, the strategy agents contain an expert system modeling their specific behavior in an optimization environment by means of rules and facts on a highly abstract level. Further, different common interaction patterns have been defined to describe the structure of a strategy network and its interactions.For managing the complexity of NSPs using multi-agent systems (MASs) efficiently, a simulation and experimentation platform has been developed. Serving as a computational steering tool, it applies MAS technology and accesses a network of various optimization strategies. As a consequence, an elegant interactive steering, a customized modeling and a powerful visualization of structural optimization processes are established. To demonstrate the far reaching applicability of the proposed approach, numerical examples are discussed, including nonlinear function and robust optimization problems. The results of the numerical experiments illustrate the potential of the agent-based strategy network approach for collaborative solving, where observed synergy effects lead to an effective and efficient solution finding.     

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.     

A goal-driven and agent-based requirements engineering framework*

The paper presents a requirements engineering framework (REF), where advanced requirements engineering techniques are combined with software quality modelling approaches to provide an environment within which the stakeholders and the analysts can easily cooperate to discover, organise, reconcile and validate the requirements for a new system. By adopting a basic and essential graphical notation, and a clear top-down methodology, REF allows for an effective involvement of the stakeholders, assisting and driving them to an early definition of the desired system's functionalities and quality attributes, while supporting the redesign of the encompassing organisational context to better exploit the new system's capabilities. As a case study, REF is applied to support the requirements engineering process for a complex software-intensive simulation system. Results demonstrate the feasibility of REF and the benefits it offers to the requirements engineering process, but also to the subsequent system development phases. As illustrated through the case study REF can, in fact, be usefully applied as a forerunner for unified modelling language (UML)-based approaches.*Part of this work was completed while the author was Senior Research Fellow with the Computing Information Systems Engineering Group, at the Royal Military College of Science, Cranfield University (UK)     

An agent-based data-flow testing approach for Web applications

In recent years, Web applications (WAs) have grown so quickly that they have already become crucial to the success of businesses. However, since they are built on Internet and open standard technologies, WAs possess their own unique features, such as dynamic behaviors, heterogeneous representations, and novel data handling mechanisms. These features provide concrete support to the success of WAs, but they bring new challenges to researchers and developers, especially in regard to testing WAs and ensuring their quality. Testing approaches for non-WAs have to be extended to handle these features before they are used in WA testing. This paper presents an agent-based approach to perform data-flow testing of WAs. More precisely, the data-flow testing will be performed by autonomous test agents at the method level, object level, and object cluster level, from low abstraction level to high abstraction level. In the process of the recommended data-flow testing, an agent-based WA testing system (WAT) will automatically generate and coordinate test agents to decompose the task of testing an entire WA into a set of subtasks that can be accomplished by test agents. The test agents, rooted in the Belief–Desire–Intention (BDI) model, cooperate with each other to complete the testing of a WA. An example is used to show the feasibility of the proposed approach.     

An agent-based framework for cooperating expert systems in concurrent engineering

This paper describes an agent-based framework with a tandem integration architecture for cooperating distributed, heterogeneous, and autonomous concurrent engineering systems. The approach has been experimented with using the prototype AGENTS system. It is demonstrated that design tools can be dynamically connected and configured to construct highly complex systems on an incremental basis, designing and proving one system at a time without bothering the rest. A major advantage of the approach is the balance between the interoperability and the autonomy of individual systems.     

Toward an agent-based and context-oriented approach for Web services composition

This paper presents an agent-based and context-oriented approach that supports the composition of Web services. A Web service is an accessible application that other applications and humans can discover and invoke to satisfy multiple needs. To reduce the complexity featuring the composition of Web services, two concepts are put forward, namely, software agent and context. A software agent is an autonomous entity that acts on behalf of users and the context is any relevant information that characterizes a situation. During the composition process, software agents engage in conversations with their peers to agree on the Web services that participate in this process. Conversations between agents take into account the execution context of the Web services. The security of the computing resources on which the Web services are executed constitutes another core component of the agent-based and context-oriented approach presented in this paper.     

基于移动Agent的信息搜索系统的研究

对传统客户/服务器模式的网络信息搜索系统的缺点进行了分析,将移动Agent技术引入信息搜索领域,阐述了Agent和移动Agent的概念,特点、开发工具,分析了其适合信息搜索的技术特点.提出了一个基于移动Agent的网络信息搜索原型系统(MAISS)来处理网络信息搜索,以实现搜索的高效率,低开销以及智能化,并时其结构及功能,实现机制和关键技术进行了深入的分析和讨论.     

An agent-based user-authentication system

Managing the necessary public and private keys in a large organization is a serious challenge. Software agents can be an adaptive and responsive mechanism for managing users trying to connect to network resources. BTexact Technologies Intelligent Systems Laboratory has developed the Phobos agent architecture. Phobos uses a distributed team of cooperative autonomous agents to collectively authenticate user access requests. The advantages are that the agents can query multiple information sources to select the level of trust to delegate to a user and that n agents must concur to authenticate the user, hence increasing overall security. Phobos provides numerous security services to automate user authentication and trust-management processes.     

DPP: An agent-based approach for distributed process planning

A changing shop floor environment characterized by larger variety of products in smaller batch sizes requires creating an intelligent and dynamic process planning system that is responsive and adaptive to the rapid adjustment of production capacity and functionality. In response to the requirement, this research proposes a new methodology of distributed process planning (DPP). The primary focus of this paper is on the architecture of the new process planning approach, using multi-agent negotiation and cooperation. The secondary focus is on the other supporting technologies such as machining feature-based planning and function block-based control. Different from traditional methods, the proposed approach uses two-level decision-making—supervisory planning and operation planning. The former focuses on product data analysis, machine selection, and machining sequence planning, while the latter considers the detailed working steps of the machining operations inside of each process plan and is accomplished by intelligent NC controllers. By the nature of decentralization, the DPP shows promise of improving system performance within the continually changing shop floor environment.     

An agent-based approach to multisensor coordination

This paper presents an automated system for multiple sensor placement based on the coordinated decisions of independent, intelligent agents. The problem domain is such that a single sensor system would not provide adequate information for a given sensor task. Hence, it is necessary to incorporate multiple sensors in order to obtain complete information. The overall goal of the system is to provide the surface coverage necessary to perform feature inspection on one or more target objects in a cluttered scene. This is accomplished by a group of cooperating intelligent sensors. In this system, the sensors are mobile, the target objects are stationary and each agent controls the position of a sensor and has the ability to communicate with other agents in the environment. By communicating desires and intentions, each agent develops a mental model of the other agents' preferences, which is used to avoid or resolve conflict situations. In this paper we utilize cameras as the sensors. The experimental results illustrate the feasibility of the autonomous deployment of the sensors and that this deployment can occur with sufficient accuracy as to allow the inspection task to be performed.     

An agent-based approach to tool integration

Tool integration is a very difficult challenge. Problems may arise at different abstraction levels and from several sources such as heterogeneity of manipulated data, incompatible interfaces, or uncoordinated services, to name just a few examples. On the other hand, applications based on the coherent composition of activities, components, services, and data from heterogeneous sources are increasingly present in our everyday lives. Consequently, tool integration takes on increasing significance.In this paper we analyze the tool-integration problem at different abstraction levels and discuss different views on a layered software architecture that we have designed specifically for a middleware that supports the execution of distributed applications for the orchestration of human/system activities. We noticed that the agent paradigm provided a suitable technology for abstraction in tool integration. Throughout the paper, the discussion refers to a case study in the bioinformatics domain.     

An interactive agent-based system for concept-based web search

Search engines are useful tools in looking for information from the Internet. However, due to the difficulties of specifying appropriate queries and the problems of keyword-based similarity ranking presently encountered by search engines, general users are still not satisfied with the results retrieved. To remedy the above difficulties and problems, in this paper we present a multi-agent framework in which an interactive approach is proposed to iteratively collect a user's feedback from the pages he has identified. By analyzing the pages gathered, the system can then gradually formulate queries to efficiently describe the content a user is looking for. In our framework, the evolution strategies are employed to evolve critical feature words for concept modeling in query formulation. The experimental results show that the framework developed is efficient and useful to enhance the quality of web search, and the concept-based semantic search can thus be achieved.     

An agent-based support system for railway station dispatching

For those railway stations without being automated, railway traffic dispatching still depends on dispatchers, especially under disturbed circumstances. In this study, an agent-based support system, named D-Agent, is developed to assist human dispatchers to make decisions in station operation. To this end, the common knowledge and possible difficulties concerning a station dispatcher in his/her routine work are firstly studied, and the D-Agent is proposed with the purpose of working out practicable solutions to these challenging tasks as a dispatcher does. Then the general model of the D-Agent is established, containing five basic modules: local database, knowledge base, skill base, reasoning mechanism and communication interfaces. The internal skills of the D-Agent are designed to execute various tasks in different scenarios. Besides, a skill extension of the D-Agent with mathematical formulations is particularly discussed in this paper, to find feasible and optimal traffic control solutions in disturbance situations such as train delays and route conflicts. The D-Agent is designed to learn from its own experimental history in applying different skills, and evaluate the skills by preference weights of alternative solutions in a particular task. This procedure allows the agent to have potential for continuous improvement. To verify the applicability of the proposed support system, a D-Agent for a terminal station of subway is simulated. The numerical example of train delays and route conflicts shows that the D-Agent can generally perform as a station dispatcher in fulfilling the specific tasks, estimate the traffic state in different operation strategies and support the decision-making of favored solutions. Significantly, it indicates that the mathematical methods can also been employed by an intelligent agent.     

Fuzzy agent-based expert system for steel making process

In this paper, a fuzzy multi-agent system is proposed for electric arc furnace steel making processes. Each process of electric arc furnace steel making is assigned to be an agent, which works independently whilst coordinates and cooperates with other acquaintance agents. Adaptive neuro-fuzzy inference system is used to generate agents’ knowledge bases. Contract net protocol is used as negotiation protocol in the proposed multi-agent system.     

An adaptive agent-based system for deregulated smart grids

The power grid is undergoing a major change due mainly to the increased penetration of renewables and novel digital instruments in the hands of the end users that help to monitor and shift their loads. Such transformation is only possible with the coupling of an information and communication technology infrastructure to the existing power distribution grid. Given the scale and the interoperability requirements of such future system, service-oriented architectures (SOAs) are seen as one of the reference models and are considered already in many of the proposed standards for the smart grid (e.g., IEC-62325 and OASIS eMIX). Beyond the technical issues of what the service-oriented architectures of the smart grid will look like, there is a pressing question about what the added value for the end user could be. Clearly, the operators need to guarantee availability and security of supply, but why should the end users care? In this paper, we explore a scenario in which the end users can both consume and produce small quantities of energy and can trade these quantities in an open and deregulated market. For the trading, they delegate software agents that can fully interoperate and interact with one another thus taking advantage of the SOA. In particular, the agents have strategies, inspired from game theory, to take advantage of a service-oriented smart grid market and give profit to their delegators, while implicitly helping balancing the power grid. The proposal is implemented with simulated agents and interaction with existing Web services. To show the advantage of the agent with strategies, we compare our approach with the “base” agent one by means of simulations, highlighting the advantages of the proposal.     

An agent-based system for bilateral contracts of energy

In this paper, an agent-based system for bilateral contracts of energy is proposed. The generating companies submit their offers to the demand companies. The demand companies also submit their bids to the generators. Each load or generator’s agent wants to match with an opponent, which offers the most valuable proposal. However, the problem of simultaneous decision-making causes decision conflicts among the agents. To overcome this conflict, we assume loads as the leaders and generators as the followers. We use Stackelberg game to match the seller and buyer agents. The negotiation process between a buyer and its potential seller will determine the power price between them. This process is carried out through a proposed combined time-behavioral protocol (TBP). With negligible changes in around the agreed price, this protocol can reduce the negotiation time considerably. After successful negotiation, the seller and buyer agents could sign a bilateral contract of energy if the market conditions allow it. The applicability of the proposed method is illustrated through a case study.