MASDScheGATS: a prototype system for dynamic scheduling

A manufacturing system has a natural dynamic nature observed through several kinds of random occurrences and perturbations on working conditions and requirements over time. For this kind of environment it is important the ability to efficient and effectively adapt, on a continuous basis, existing schedules according to the referred disturbances, keeping performance levels. The application of Meta-Heuristics and Multi-Agent Systems to the resolution of this class of real world scheduling problems seems really promising. This paper presents a prototype for MASDScheGATS (Multi-Agent System for Distributed Manufacturing Scheduling with Genetic Algorithms and Tabu Search).

Multi-agent electricity market simulation with dynamic strategies & virtual power producers

Distributed energy resources will provide a significant amount of the electricity generation and will be a normal profitable business. In the new decentralized grid, customers will be among the many decentralized players and may even help to co-produce the required energy services such as demand-side management and load shedding. So, they will gain the opportunity to be more active market players. The aggregation of DG plants gives place to a new concept: the Virtual Power Producer (VPP). VPPs can reinforce the importance of these generation technologies making them valuable in electricity markets. In this paper we propose the improvement of MASCEM, a multi-agent simulation tool to study negotiations in electricity spot markets based on different market mechanisms and behavior strategies, in order to take account of decentralized players such as VPP.

MASCEM: electricity markets simulation with strategic agents

Electricity markets are complex environments, involving numerous entities trying to obtain the best advantages and profits while limited by power-network characteristics and constraints.1 The restructuring and consequent deregulation of electricity markets introduced a new economic dimension to the power industry. Some observers have criticized the restructuring process, however, because it has failed to improve market efficiency and has complicated the assurance of reliability and fairness of operations. To study and understand this type of market, we developed the Multiagent Simulator of Competitive Electricity Markets (MASCEM) platform based on multiagent simulation. The MASCEM multiagent model includes players with strategies for bid definition, acting in forward, day-ahead, and balancing markets and considering both simple and complex bids. Our goal with MASCEM was to simulate as many market models and player types as possible. This approach makes MASCEM both a short- and mediumterm simulation as well as a tool to support long-term decisions, such as those taken by regulators. This article proposes a new methodology integrated in MASCEM for bid definition in electricity markets. This methodology uses reinforcement learning algorithms to let players perceive changes in the environment, thus helping them react to the dynamic environment and adapt their bids accordingly.

Collective intelligence on dynamic manufacturing scheduling optimization

Swarm Intelligence (SI) is a growing research field of Artificial Intelligence (AI). SI is the general term for several computational techniques which use ideas and get inspiration from the social behaviours of insects and of other animals. This paper presents hybridization and combination of different AI approaches, like Bio-Inspired Techniques (BIT), Multi-Agent systems (MAS) and Machine Learning Techniques (ML T). The resulting system is applied to the problem of jobs scheduling to machines on dynamic manufacturing environments.

Meta-heuristics tunning using CBR for dynamic scheduling

This paper addresses the problem of Biological Inspired Optimization Techniques (BIT) parameterization, considering the importance of this issue in the design of BIT especially when considering real world situations, subject to external perturbations. A learning module with the objective to permit a Multi-Agent Scheduling System to automatically select a Meta-heuristic and its parameterization to use in the optimization process is proposed. For the learning process, Casebased Reasoning was used, allowing the system to learn from experience, in the resolution of similar problems. Analyzing the obtained results we conclude about the advantages of its use.

Self-optimization aspects for dynamic scheduling

Scheduling is a critical function that is present throughout many industries and applications. A great need exists for developing scheduling approaches that can be applied to a number of different scheduling problems with significant impact on performance of business organizations. A challenge is emerging in the design of scheduling support systems for manufacturing environments where dynamic adaptation and optimization become increasingly important. At this scenario, self-optimizing arise as the ability of the agent to monitor its state and performance and proactively tune itself to respond to environmental stimuli.

Self-managing agents for dynamic scheduling in manufacturing

The main purpose of this paper is to propose a Multi-Agent Autonomic and Bio-Inspired based framework with selfmanaging capabilities to solve complex scheduling problems using cooperative negotiation. Scheduling resolution requires the intervention of highly skilled human problem-solvers. This is a very hard and challenging domain because current systems are becoming more and more complex, distributed, interconnected and subject to rapidly changing. A natural Autonomic Computing (AC) evolution in relation to Current Computing is to provide systems with Self-Managing ability with a minimum human interference.

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.

Dynamic power- and failure-aware cloud resources allocation for Sets of independent tasks

Cloud computing is increasingly being adopted in different scenarios, like social networking, business applications, scientific experiments, etc. Relying in virtualization technology, the construction of these computing environments targets improvements in the infrastructure, such as power-efficiency and fulfillment of users’ SLA specifications. The methodology usually applied is packing all the virtual machines on the proper physical servers. However, failure occurrences in these networked computing systems can induce substantial negative impact on system performance, deviating the system from ours initial objectives. In this work, we propose adapted algorithms to dynamically map virtual machines to physical hosts, in order to improve cloud infrastructure power-efficiency, with low impact on users’ required performance. Our decision making algorithms leverage proactive fault-tolerance techniques to deal with systems failures, allied with virtual machine technology to share nodes resources in an accurately and controlled manner. The results indicate that our algorithms perform better targeting power-efficiency and SLA fulfillment, in face of cloud infrastructure failures.

Mudanças climáticas nas regiões insulares

Tese de Doutoramento, Física, 27 de Novembro de 2013, Universidade dos Açores.

Identity – towards a conceptualization

The development of economical relations increases the interaction between organizations and stakeholders. It is no more acceptable to manage an organization under a transactional perspective where suppliers had a fundamental role. Nowadays organizations are being managed under a relational perspective where relations and relationship management in general have consequences in identity management (Hakansson e Snehota, 1989, 1995). A correct perception and management of identity is necessary to achieve distinctiveness in the competitive environment. This way, identity is influenced by relations with stakeholders in general and particularly with competitors. The ICIG concept states that identity is related with the values of the organization and it helps creating distinctiveness in the competitive environment (Van Riel, Balmer, 1997); Baker and Balmer (1997) state that identity is what the organization is; Suvatjis and de Chernatony (2005) refer that expressing identity is a dynamic process that evolves the use of a management model to face context changes; Kapferer (1991) states that brand identity is the project, the self conception of the brand. After reviewing and confronting literature under the plethora of identities’ concepts and perspectives (He, Balmer, 2007) one can’t find an integrative answer with all the elements that contribute to identity of organizations. The authors are strongly interested to contribute to the elimination of this limitation and to answer to strategic management needs. In a marketing context one can find: - the corporate identity approach that is focused in the distinctive attributes of an organization (Abratt, Balmer, Marwick e Fill, Stuart, Balmer and Gray, Alessandri, Suvatjis and de Chernatony) - the brand identity approach (related with the application of corporate identity studies to brands) - Kapferer, Semprini, Aaker, de Chernatony). Kapferer (1991), one of the most prolific authors in this field was the first author to integrate identity in a brand concept. In his view, identity is an emission concept. This idea is shared also by Aaker (1996). Yet, identity has to be managed in a competitive environment which is constantly changing. After reviewing and confronting literature, authors select concepts that are generally accepted by the investigators in order to design a model to analyze and manage identity: - corporate identity models: personality, image/reputation, culture, philosophy, mission, strategy, structure, communication - some of these concepts derive from identity models and others from identity management models; - brand identity models – Kapferer (1991, 2008) identity prism, witch is basis of literature in this field: culture, physical facet, personality, relationship (between brand and consumer), reflected consumer, consumers` self-concept. After discussion authors decide to include other concept in line with other authors` view: country of origin (Aaker, 1996). A discussion eliminates the twin concepts and the final selection is as follows: personality, image/reputation, culture (including philosophy and mission), strategy, structure, communication, culture, physical facet, relationship (between brand and consumer), reflected consumer, consumers` self-concept and according to authors` reflections “relationships” deriving from competitors` actions in competitive environment. Competitors’ actions and decisions have a stronger influence in the organizations` positioning than any other stakeholder as stated before. This is a work in progress towards a new model in identity analysis and management so an exploratory study will follow inquiring experts on identity in order to evaluate these concepts and correct the theoretical perspectives.

Avaliação do stock de Abalones: uma pesca sustentável

Jornadas "Ciência nos Açores – que futuro? Tema Ciências Naturais e Ambiente", Ponta Delgada, 7-8 de Junho de 2013.

Evidence of long-term changes in the distribution of key intertidal species

World Congress of Malacology, Ponta Delgada, July 22-28, 2013.

Efeitos da timectomia neonatal sobre o dimorfismo sexual esquelético e concentração plasmática de leptina em ratos

Pós-graduação em Ciências Fisiológicas - FOA

Economic burden of expected epidemiological changes in diseases related to tobacco, Mexico

OBJECTIVE: To determine health care costs and economic burden of epidemiological changes in diseases related to tobacco consumption. METHODS: A time-series analysis in Mexico (1994-2005) was carried out on seven health interventions: chronic obstructive pulmonary diseases, lung cancer with and without surgical intervention, asthma in smokers and non-smokers, full treatment course with nicotine gum, and full treatment course with nicotine patch. According with Box-Jenkins methodology, probabilistic models were developed to forecast the expected changes in the epidemiologic profile and the expected changes in health care services required for selected interventions. Health care costs were estimated following the instrumentation methods and validated with consensus technique. RESULTS: A comparison of the economic impact in 2006 vs. 2008 showed 20-90% increase in expected cases depending on the disease (p<0.05), and 25-93% increase in financial requirements (p<0.01). The study data suggest that changes in the demand for health services for patients with respiratory diseases related to tobacco consumption will continue showing an increasing trend. CONCLUSIONS: In economic terms, the growing number of cases expected during the study period indicates a process of internal competition and adds an element of intrinsic competition in the management of preventive and curative interventions. The study results support the assumption that if preventive programs remain unchanged, the increasing demands for curative health care may cause great financial and management challenges to the health care system of middle-income countries like Mexico.