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.

Negotiation mechanism for self-organized scheduling system with collective intelligence

Current Manufacturing Systems challenges due to international economic crisis, market globalization and e-business trends, incites the development of intelligent systems to support decision making, which allows managers to concentrate on high-level tasks management while improving decision response and effectiveness towards manufacturing agility. This paper presents a novel negotiation mechanism for dynamic scheduling based on social and collective intelligence. Under the proposed negotiation mechanism, agents must interact and collaborate in order to improve the global schedule. Swarm Intelligence (SI) is considered a general aggregation term for several computational techniques, which use ideas and inspiration from the social behaviors of insects and other biological systems. This work is primarily concerned with negotiation, where multiple self-interested agents can reach agreement over the exchange of operations on competitive resources. Experimental analysis was performed in order to validate the influence of negotiation mechanism in the system performance and the SI technique. Empirical results and statistical evidence illustrate that the negotiation mechanism influence significantly the overall system performance and the effectiveness of Artificial Bee Colony for makespan minimization and on the machine occupation maximization.

Representations of gender in the writings of St. Francis Xavier: an interdisciplinary approach

Francis Xavier’s Letters and Writings are eloquent narratives of a journey that absorbed the Saint’s entire life. His experiences and idiosyncrasies, values and categorizations are presented in a clear literate discourse. The missionary is rarely neutral in his opinions as he sustains his unmistakable and omnipresent objective: the conversion of peoples and the expansion of the Society of Jesus. Parallel with this objective, the reader is introduced to the individuals that Xavier meets or that he summons in his epistolary discourse. Letters and Writings presents us with a structured narrative peopled by all those who are subject to and objects of Xavier’s apostolic mission, by helpful and unhelpful persons of influence, and by leading and secondary actors. What is then the position of women, in the collective sense as well as in the individual sense, in the travels and goals that are the centre of Xavier’s Letters and Writings? What is the role of women, that secondary and suppressed term in the man/woman binomial, a dichotomy similar to the civilized/savage and European/native binomials that punctuate Xavier’s narratives and the historic context of his letters? Women are not absent from his writings, but it would be naïve to argue in favour of the author’s misogyny as much as of his “profound knowledge of the female heart”, to quote from Paulo Durão in "Women in the Letters of Saint Francis Xavier" (1952), the only paper on this subject published so far. We denote four great categories of women in the Letters and Writings: European Women, Converted Women, Women Who Profess another Religion, and Women as the Agents and Objects of Sin, the latter of which traverses the other three categories. They all depend on the context, circumstances and judgements of value that the author chooses to highlight and articulate.

Impacto das comunidades de consumidores no valor das marcas

International Congress Marketing Trends Annual Conference in Paris, 17 – 19 January 2013

Estudo da norma contabilística e de relato financeiro nº 13 – interesses em empreendimentos conjuntos e investimentos em associadas e suas implicações fiscais e de auditoria

Dissertação apresentada ao Instituto Superior de Contabilidade e Administração do Porto para a obtenção do Grau de Mestre em Auditoria Orientada pelo Dr. José da Silva Fernandes

Cooperative scheduling system with emergent swarm based behavior

This paper presents a Swarm based Cooperation Mechanism for scheduling optimization. We intend to conceptualize real manufacturing systems as interacting autonomous entities in order to support decision making in agile manufacturing environments. Agents coordinate their actions automatically without human supervision considering a common objective – global scheduling solution taking advantages from collective behavior of species through implicit and explicit cooperation. The performance of the cooperation mechanism will be evaluated consider implicit cooperation at first stage through ACS, PSO and ABC algorithms and explicit through cooperation mechanism application.

ISEM: a multi-agent system that simulates competitive electronic marketplaces

With the increasing importance of large commerce across the Internet it is becoming increasingly evident that in a few years the Iternet will host a large number of interacting software agents. a vast number of them will be economically motivated, and will negociate a variety of goods and services. It is therefore important to consider the economic incentives and behaviours of economic software agents, and to use all available means to anticipate their collective interactions. This papers addresses this concern by presenting a multi-agent market simulator designed for analysing agent market strategies based on a complete understanding of buyer and seller behaviours, preference models and pricing algorithms, consideting risk preferences. The system includes agents that are capable of increasing their performance with their own experience, by adapting to the market conditions. The results of the negotiations between agents are analysed by data minig algorithms in order to extract rules that give agents feedback to imprive their strategies.