Scheduling in holonic manufacturing systems

This chapter presents some of the issues with holonic manufacturing systems. It starts by presenting the current manufacturing scenario and trends and then provides some background information on the holonic concept and its application to manufacturing. The current limitations and future trends of manufacturing suggest more autonomous and distributed organisations for manufacturing systems; holonic manufacturing systems are proposed as a way to achieve such autonomy and decentralisation. After a brief literature survey a specific research work is presented to handle scheduling in holonic manufacturing systems. This work is based on task and resource holons that cooperate with each other based on a variant of the contract net protocol that allow the propagation of constraints between operations in the execution plan. The chapter ends by presenting some challenges and future opportunities of research.

VirtualECare: group decision supported by idea generation and argumentation

In the last years there has been a considerable increase in the number of people in need of intensive care, especially among the elderly, a phenomenon that is related to population ageing (Brown 2003). However, this is not exclusive of the elderly, as diseases as obesity, diabetes, and blood pressure have been increasing among young adults (Ford and Capewell 2007). As a new fact, it has to be dealt with by the healthcare sector, and particularly by the public one. Thus, the importance of finding new and cost effective ways for healthcare delivery are of particular importance, especially when the patients are not to be detached from their environments (WHO 2004). Following this line of thinking, a VirtualECare Multiagent System is presented in section 2, being our efforts centered on its Group Decision modules (Costa, Neves et al. 2007) (Camarinha-Matos and Afsarmanesh 2001).On the other hand, there has been a growing interest in combining the technological advances in the information society - computing, telecommunications and knowledge – in order to create new methodologies for problem solving, namely those that convey on Group Decision Support Systems (GDSS), based on agent perception. Indeed, the new economy, along with increased competition in today’s complex business environments, takes the companies to seek complementarities, in order to increase competitiveness and reduce risks. Under these scenarios, planning takes a major role in a company life cycle. However, effective planning depends on the generation and analysis of ideas (innovative or not) and, as a result, the idea generation and management processes are crucial. Our objective is to apply the GDSS referred to above to a new area. We believe that the use of GDSS in the healthcare arena will allow professionals to achieve better results in the analysis of one’s Electronically Clinical Profile (ECP). This attainment is vital, regarding the incoming to the market of new drugs and medical practices, which compete in the use of limited resources.

A study on the authentication method for TAmI in ambient intelligence (secure group decision making toolkit)

It is difficult to get the decision about an opinion after many users get the meeting in same place. It used to spend too much time in order to find solve some problem because of the various opinions of each other. TAmI (Group Decision Making Toolkit) is the System to Group Decision in Ambient Intelligence [1]. This program was composed with IGATA [2], WebMeeting and the related Database system. But, because it is sent without any encryption in IP / Password, it can be opened to attacker. They can use the IP / Password to the bad purpose. As the result, although they make the wrong result, the joined member can’t know them. Therefore, in this paper, we studied the applying method of user’s authentication into TAmI.

Modelling group decision simulation through argumentation

Group decision making plays an important role in today’s organisations. The impact of decision making is so high and complex, that rarely the decision making process is made individually. In Group Decision Argumentation, there is a set of participants, with different profiles and expertise levels, that exchange ideas or engage in a process of argumentation and counter-argumentation, negotiate, cooperate, collaborate or even discuss techniques and/or methodologies for problem solving. In this paper, it is proposed a Multi-Agent simulator for the behaviour representation of group members in a decision making process. Agents behave depending on rational and emotional intelligence and use persuasive argumentation to convince and make alternative choices.

Cooperation mechanism for team-work based multi-agent system in dynamic scheduling through meta-heuristics

This paper describes a Multi-agent Scheduling System that assumes the existence of several Machines Agents (which are decision-making entities) distributed inside the Manufacturing System that interact and cooperate with other agents in order to obtain optimal or near-optimal global performances. Agents have to manage their internal behaviors and their relationships with other agents via cooperative negotiation in accordance with business policies defined by the user manager. Some Multi Agent Systems (MAS) organizational aspects are considered. An original Cooperation Mechanism for a Team-work based Architecture is proposed to address dynamic scheduling using Meta-Heuristics.

ABS4GD: a multi-agent system that simulates group decision processes considering emotional and argumentative aspects

Emotion although being an important factor in our every day life it is many times forgotten in the development of systems to be used by persons. In this work we present an architecture for a ubiquitous group decision support system able to support persons in group decision processes. The system considers the emotional factors of the intervenient participants, as well as the argumentation between them. Particular attention will be taken to one of components of this system: the multi-agent simulator, modeling the human participants, considering emotional characteristics, and allowing the exchanges of hypothetic arguments among the participants.

Personality, emotion, and mood in agent-based group decision making

Group decision making plays an important role in organizations, especially in the present-day economy that demands high-quality, yet quick decisions. Group decision-support systems (GDSSs) are interactive computer-based environments that support concerted, coordinated team efforts toward the completion of joint tasks. The need for collaborative work in organizations has led to the development of a set of general collaborative computer-supported technologies and specific GDSSs that support distributed groups (in time and space) in various domains. However, each person is unique and has different reactions to various arguments. Many times a disagreement arises because of the way we began arguing, not because of the content itself. Nevertheless, emotion, mood, and personality factors have not yet been addressed in GDSSs, despite how strongly they influence results. Our group’s previous work considered the roles that emotion and mood play in decision making. In this article, we reformulate these factors and include personality as well. Thus, this work incorporates personality, emotion, and mood in the negotiation process of an argumentbased group decision-making process. Our main goal in this work is to improve the negotiation process through argumentation using the affective characteristics of the involved participants. Each participant agent represents a group decision member. This representation lets us simulate people with different personalities. The discussion process between group members (agents) is made through the exchange of persuasive arguments. Although our multiagent architecture model4 includes two types of agents—the facilitator and the participant— this article focuses on the emotional, personality, and argumentation components of the participant agent.

Context-aware emotion-based model for group decision making

Involving groups in important management processes such as decision making has several advantages. By discussing and combining ideas, counter ideas, critical opinions, identified constraints, and alternatives, a group of individuals can test potentially better solutions, sometimes in the form of new products, services, and plans. In the past few decades, operations research, AI, and computer science have had tremendous success creating software systems that can achieve optimal solutions, even for complex problems. The only drawback is that people don’t always agree with these solutions. Sometimes this dissatisfaction is due to an incorrect parameterization of the problem. Nevertheless, the reasons people don’t like a solution might not be quantifiable, because those reasons are often based on aspects such as emotion, mood, and personality. At the same time, monolithic individual decisionsupport systems centered on optimizing solutions are being replaced by collaborative systems and group decision-support systems (GDSSs) that focus more on establishing connections between people in organizations. These systems follow a kind of social paradigm. Combining both optimization- and socialcentered approaches is a topic of current research. However, even if such a hybrid approach can be developed, it will still miss an essential point: the emotional nature of group participants in decision-making tasks. We’ve developed a context-aware emotion based model to design intelligent agents for group decision-making processes. To evaluate this model, we’ve incorporated it in an agent-based simulator called ABS4GD (Agent-Based Simulation for Group Decision), which we developed. This multiagent simulator considers emotion- and argument based factors while supporting group decision-making processes. Experiments show that agents endowed with emotional awareness achieve agreements more quickly than those without such awareness. Hence, participant agents that integrate emotional factors in their judgments can be more successful because, in exchanging arguments with other agents, they consider the emotional nature of group decision making.

LAID - a smart decision room with ambient intelligence for group decision making and argumentation support considering emotional aspects

Decision Making is one of the most important activities of the human being. Nowadays decisions imply to consider many different points of view, so decisions are commonly taken by formal or informal groups of persons. Groups exchange ideas or engage in a process of argumentation and counter-argumentation, negotiate, cooperate, collaborate or even discuss techniques and/or methodologies for problem solving. Group Decision Making is a social activity in which the discussion and results consider a combination of rational and emotional aspects. In this paper we will present a Smart Decision Room, LAID (Laboratory of Ambient Intelligence for Decision Making). In LAID environment it is provided the support to meeting room participants in the argumentation and decision making processes, combining rational and emotional aspects.

Modeling group decision meeting participants with an Agent-based approach

This paper aims to present a multi-agent model for a simulation, whose goal is to help one specific participant of multi-criteria group decision making process.This model has five main intervenient types: the human participant, who is using the simulation and argumentation support system; the participant agents, one associated to the human participant and the others simulating the others human members of the decision meeting group; the directory agent; the proposal agents, representing the different alternatives for a decision (the alternatives are evaluated based on criteria); and the voting agent responsiblefor all voting machanisms.At this stage it is proposed a two phse algorithm. In the first phase each participantagent makes his own evaluation of the proposals under discussion, and the voting agent proposes a simulation of a voting process.In the second phase, after the dissemination of the voting results,each one ofthe partcipan agents will argue to convince the others to choose one of the possible alternatives. The arguments used to convince a specific participant are dependent on agent knowledge about that participant. This two-phase algorithm is applied iteratively.

Agent based simulation for group formation

Group decision making plays an important role in today’s organisations. The impact of decision making is so high and complex, that rarely the decision making process is made just by one individual. The simulation of group decision making through a Multi-Agent System is a very interesting research topic. The purpose of this paper it to specify the actors involved in the simulation of a group decision, to present a model to the process of group formation and to describe the approach made to implement that model. In the group formation model it is considered the existence of incomplete and negative information, which was identified as crucial to make the simulation closer to the reality.

Group decision making and Quality-of-information in e-Health systems

Knowledge is central to the modern economy and society. Indeed, the knowledge society has transformed the concept of knowledge and is more and more aware of the need to overcome the lack of knowledge when has to make options or address its problems and dilemmas. One’s knowledge is less based on exact facts and more on hypotheses, perceptions or indications. Even when we use new computational artefacts and novel methodologies for problem solving, like the use of Group Decision Support Systems (GDSSs), the question of incomplete information is in most of the situations marginalized. On the other hand, common sense tells us that when a decision is made it is impossible to have a perception of all the information involved and the nature of its intrinsic quality. Therefore, something has to be made in terms of the information available and the process of its evaluation. It is under this framework that a Multi-valued Extended Logic Programming language will be used for knowledge representation and reasoning, leading to a model that embodies the Quality-of-Information (QoI) and its quantification, along the several stages of the decision-making process. In this way, it is possible to provide a measure of the value of the QoI that supports the decision itself. This model will be here presented in the context of a GDSS for VirtualECare, a system aimed at sustaining online healthcare services.

VirtualECare: group support in collaborative networks organizations for digital homecare

Collaborative Work plays an important role in today’s organizations, especially in areas where decisions must be made. However, any decision that involves a collective or group of decision makers is, by itself complex, but is becoming recurrent in recent years. In this work we present the VirtualECare project, an intelligent multi-agent system able to monitor, interact and serve its customers, which are, normally, in need of care services. In last year’s there has been a substantially increase on the number of people needed of intensive care, especially among the elderly, a phenomenon that is related to population ageing. However, this is becoming not exclusive of the elderly, as diseases like obesity, diabetes and blood pressure have been increasing among young adults. This is a new reality that needs to be dealt by the health sector, particularly by the public one. Given this scenarios, the importance of finding new and cost effective ways for health care delivery are of particular importance, especially when we believe they should not to be removed from their natural “habitat”. Following this line of thinking, the VirtualECare project will be presented, like similar ones that preceded it. Recently we have also assisted to a growing interest in combining the advances in information society - computing, telecommunications and presentation – in order to create Group Decision Support Systems (GDSS). Indeed, the new economy, along with increased competition in today’s complex business environments, takes the companies to seek complementarities in order to increase competitiveness and reduce risks. Under these scenarios, planning takes a major role in a company life. However, effective planning depends on the generation and analysis of ideas (innovative or not) and, as a result, the idea generation and management processes are crucial. Our objective is to apply the above presented GDSS to a new area. We believe that the use of GDSS in the healthcare arena will allow professionals to achieve better results in the analysis of one’s Electronically Clinical Profile (ECP). This achievement is vital, regarding the explosion of knowledge and skills, together with the need to use limited resources and get better results.

Análise e melhoria de processo de pintura e vulcanização na Continental

A indústria automóvel é um dos setores mais exigentes do mercado global, por este motivo empresas como a Continental Mabor S.A, líderes de mercado, necessitam estar na linha da frente no que toca a programas de melhoria contínua e de uma gestão orientada para um crescimento rentável e sustentado. Nesta perspetiva, este estudo de dissertação tem como objetivo encontrar uma solução para a gestão de stock e FiFo (First in First out) de pneus em verde na supracitada empresa, situada em Lousado, Vila Nova de Famalicão. Este projeto de dissertação iniciou-se com uma análise e diagnóstico do processo produtivo do pneu, entre a Construção e a Vulcanização. Nesta análise, foi possível identificar vários problemas, sendo o mais crítico associado à logística interna de transporte do pneu “em curso”, de fabrico entre as fases do mesmo, Construção e Vulcanização. Devido a condicionantes estruturais e de organização, a logística interna de transporte entre estes dois sectores enfrenta estrangulamentos nos fluxos, a falta de espaço para acomodar o material em curso, problemas organizacionais de controlo e monitorização do processo produtivo, dificuldades de regulação do fluxo e localização dos carros de transporte dos pneus em verde. Face aos problemas detetados ao longo do estudo, foram analisadas várias soluções para a resolução ou minimização dos mesmos. Entre as soluções propostas salientam-se: o alargamento do sistema de transporte por tapetes rolantes GTC (Green Tire Conveying) a todos os módulos de construção. Esta solução diminui o fluxo de carros para a área da construção, descongestionando a zona próxima do sistema de carregamento automático GTAL (Green Tire Automatic Loading) na vulcanização. A implementação dum sistema Wi-Fi RFID, que permite identificar e localizar artigos em curso utilizando etiquetas inteligentes numa rede wireless, conseguindo melhorar a programação de produção e o respetivo sequenciamento. Sabendo também que a Continental se encontra numa fase de expansão, designada Projeto Route 17/20, as soluções propostas tomaram em consideração essa nova realidade futura. Assim, foram estudados e propostos novos layouts para esse atual processo. Nestes novos layouts, procurou-se uma reorganização dos processos de fabrico, bem como um redimensionamento dos espaços de parqueamento de carros de pneus verdes adequado aos volumes produtivos. De igual forma, adequou-se os espaços físicos à possível implementação de um sistema de FiFo de pneus em verde na planta fabril, quando concluída a expansão. Este trabalho de dissertação apresenta como vantagens diretas da sua implementação: gerar a menor perturbação no atual método de trabalho seguido na empresa; previsivelmente aumentar a eficiência do processo produtivo; potenciar o crescimento tecnológico programado pela empresa; e oferecer uma boa relação custo/benefício no investimento necessário. Como apreciação final, pode-se concluir que este estudo foi finalizado com sucesso, visto que as soluções propostas foram apreciadas positivamente pela Administração da Continental Mabor S.A. e estão correntemente a ser avaliadas pelo grupo.

Stochastic short-term maintenance scheduling of GENCOs in an oligopolistic electricity market

In the proposed model, the independent system operator (ISO) provides the opportunity for maintenance outage rescheduling of generating units before each short-term (ST) time interval. Long-term (LT) scheduling for 1 or 2 years in advance is essential for the ISO and the generation companies (GENCOs) to decide their LT strategies; however, it is not possible to be exactly followed and requires slight adjustments. The Cournot-Nash equilibrium is used to characterize the decision-making procedure of an individual GENCO for ST intervals considering the effective coordination with LT plans. Random inputs, such as parameters of the demand function of loads, hourly demand during the following ST time interval and the expected generation pattern of the rivals, are included as scenarios in the stochastic mixed integer program defined to model the payoff-maximizing objective of a GENCO. Scenario reduction algorithms are used to deal with the computational burden. Two reliability test systems were chosen to illustrate the effectiveness of the proposed model for the ST decision-making process for future planned outages from the point of view of a GENCO.