Negotiation mechanism for self-organized scheduling system

This paper presents a negotiation mechanism for Dynamic Scheduling based on Swarm Intelligence (SI). Under the new negotiation mechanism, agents must compete to obtain a global schedule. SI is the general term for several computational techniques which use ideas and get inspiration from the social behaviors of insects and other animals. This work is concerned with negotiation, the process through which multiple selfinterested agents can reach agreement over the exchange of operations on competitive resources.

Cooperative intelligent system for manufacturing scheduling

Hybridization of intelligent systems is a promising research field of computational intelligence focusing on combinations of multiple approaches to develop the next generation of intelligent systems. In this paper we will model a Manufacturing System by means of Multi-Agent Systems and Meta-Heuristics technologies, where each agent may represent a processing entity (machine). The objective of the system is to deal with the complex problem of Dynamic Scheduling in Manufacturing Systems.

Server-based scheduling of parallel real-time tasks

Multicore platforms have transformed parallelism into a main concern. Parallel programming models are being put forward to provide a better approach for application programmers to expose the opportunities for parallelism by pointing out potentially parallel regions within tasks, leaving the actual and dynamic scheduling of these regions onto processors to be performed at runtime, exploiting the maximum amount of parallelism. It is in this context that this paper proposes a scheduling approach that combines the constant-bandwidth server abstraction with a priority-aware work-stealing load balancing scheme which, while ensuring isolation among tasks, enables parallel tasks to be executed on more than one processor at a given time instant.

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.

Scalable Intelligence for Scheduling Systems

A personalização é um aspeto chave de uma interação homem-computador efetiva. Numa era em que existe uma abundância de informação e tantas pessoas a interagir com ela, de muitas maneiras, a capacidade de se ajustar aos seus utilizadores é crucial para qualquer sistema moderno. A criação de sistemas adaptáveis é um domínio bastante complexo que necessita de métodos muito específicos para ter sucesso. No entanto, nos dias de hoje ainda não existe um modelo ou arquitetura padrão para usar nos sistemas adaptativos modernos. A principal motivação desta tese é a proposta de uma arquitetura para modelação do utilizador que seja capaz de incorporar diferentes módulos necessários para criar um sistema com inteligência escalável com técnicas de modelação. Os módulos cooperam de forma a analisar os utilizadores e caracterizar o seu comportamento, usando essa informação para fornecer uma experiência de sistema customizada que irá aumentar não só a usabilidade do sistema mas também a produtividade e conhecimento do utilizador. A arquitetura proposta é constituída por três componentes: uma unidade de informação do utilizador, uma estrutura matemática capaz de classificar os utilizadores e a técnica a usar quando se adapta o conteúdo. A unidade de informação do utilizador é responsável por conhecer os vários tipos de indivíduos que podem usar o sistema, por capturar cada detalhe de interações relevantes entre si e os seus utilizadores e também contém a base de dados que guarda essa informação. A estrutura matemática é o classificador de utilizadores, e tem como tarefa a sua análise e classificação num de três perfis: iniciado, intermédio ou avançado. Tanto as redes de Bayes como as neuronais são utilizadas, e uma explicação de como as preparar e treinar para lidar com a informação do utilizador é apresentada. Com o perfil do utilizador definido torna-se necessária uma técnica para adaptar o conteúdo do sistema. Nesta proposta, uma abordagem de iniciativa mista é apresentada tendo como base a liberdade de tanto o utilizador como o sistema controlarem a comunicação entre si. A arquitetura proposta foi desenvolvida como parte integrante do projeto ADSyS - um sistema de escalonamento dinâmico - utilizado para resolver problemas de escalonamento sujeitos a eventos dinâmicos. Possui uma complexidade elevada mesmo para utilizadores frequentes, daí a necessidade de adaptar o seu conteúdo de forma a aumentar a sua usabilidade. Com o objetivo de avaliar as contribuições deste trabalho, um estudo computacional acerca do reconhecimento dos utilizadores foi desenvolvido, tendo por base duas sessões de avaliação de usabilidade com grupos de utilizadores distintos. Foi possível concluir acerca dos benefícios na utilização de técnicas de modelação do utilizador com a arquitetura proposta.

An unequivocal normalization-based paradigm to solve dynamic economic and emission active-reactive OPF (optimal power flow)

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Self-optimizing through CBR learning

In this paper, we foresee the use of Multi-Agent Systems for supporting dynamic and distributed scheduling in Manufacturing Systems. We also envisage the use of Autonomic properties in order to reduce the complexity of managing systems and human interference. By combining Multi-Agent Systems, Autonomic Computing, and Nature Inspired Techniques we propose an approach for the resolution of dynamic scheduling problem, with Case-based Reasoning Learning capabilities. The objective is to permit a system to be able to automatically adopt/select a Meta-heuristic and respective parameterization considering scheduling characteristics. From the comparison of the obtained results with previous results, we conclude about the benefits of its use.

A capacity sharing and stealing strategy for open real-time systems

This paper focuses on the scheduling of tasks with hard and soft real-time constraints in open and dynamic real-time systems. It starts by presenting a capacity sharing and stealing (CSS) strategy that supports the coexistence of guaranteed and non-guaranteed bandwidth servers to efficiently handle soft-tasks’ overloads by making additional capacity available from two sources: (i) reclaiming unused reserved capacity when jobs complete in less than their budgeted execution time and (ii) stealing reserved capacity from inactive non-isolated servers used to schedule best-effort jobs. CSS is then combined with the concept of bandwidth inheritance to efficiently exchange reserved bandwidth among sets of inter-dependent tasks which share resources and exhibit precedence constraints, assuming no previous information on critical sections and computation times is available. The proposed Capacity Exchange Protocol (CXP) has a better performance and a lower overhead when compared against other available solutions and introduces a novel approach to integrate precedence constraints among tasks of open real-time systems.

La qualità erogata da un'azienda di trasporto collettivo in ambito urbano: calcolo del livello di servizio delle principali linee di ATC (BO)

Oggetto di questa tesi è lo studio della qualità del servizio di trasporto erogato che condiziona la qualità percepita dall’utente, poiché spesso proprio a causa di un errato processo di pianificazione e gestione della rete, molte aziende non sono in grado di consolidare un alto livello di efficienza che permetta loro di attrarre e servire la crescente domanda. Per questo motivo, si è deciso di indagare sugli aspetti che determinano la qualità erogata e sui fattori che la influenzano, anche attraverso la definizione di alcuni indicatori rappresentativi del servizio erogato. L’area di studio considerata è stata quella urbana di Bologna, e sono state prese in esame due linee di ATC, la 19 e la 27, caratterizzate entrambe da una domanda di trasporto molto elevata. L’interesse è ricaduto in modo particolare sugli aspetti legati alla regolarità del servizio, ovvero al rispetto della cadenza programmata delle corse e alla puntualità, ossia il rispetto dell’orario programmato delle stesse. Proprio da questi due aspetti, infatti, dipende in larga misura la percezione della qualità che gli utenti hanno del servizio di trasporto collettivo. Lo studio è stato condotto sulla base di dati raccolti attraverso due campagne di rilevamento, una effettuata nel mese di maggio dell’anno 2008 e l’altra nel mese di settembre dello stesso anno. La scelta del periodo, della zona e delle modalità di rilevamento è strettamente connessa all’obiettivo prefissato. Il servizio è influenzato dalle caratteristiche del sistema di trasporto: sia da quelle legate alla domanda che da quelle legate all’offerta. Nel caso della domanda di trasporto si considera l’influenza sul servizio del numero di passeggeri saliti e del tempo di sosta alle fermate. Nel caso dell’offerta di trasporto si osservano soprattutto gli aspetti legati alla rete di trasporto su cui si muovono gli autobus, analizzando quindi i tempi di movimento e le velocità dei mezzi, per vedere come le caratteristiche dell’infrastruttura possano condizionare il servizio. A tale proposito è opportuno dire che, mentre i dati della prima analisi ci sono utili per lo studio dell’influenza del tempo di sosta sull’intertempo, nella seconda analisi si vuole cercare di effettuare ulteriori osservazioni sull’influenza del tempo di movimento sulla cadenza, prendendo in esame altri elementi, come ad esempio tratti di linea differenti rispetto al caso precedente. Un’attenzione particolare, inoltre, verrà riservata alla verifica del rispetto della cadenza, dalla quale scaturisce la definizione del livello di servizio per ciò che riguarda la regolarità. Per quest’ultima verrà, inoltre, determinato anche il LOS relativo alla puntualità. Collegato al problema del rispetto della cadenza è il fenomeno dell’accodamento: questo si verifica quando i mezzi di una stessa linea arrivano contemporaneamente ad una fermata uno dietro l’altro. L’accodamento ha, infatti, origine dal mancato rispetto della cadenza programmata tra i mezzi ed è un’evidente manifestazione del mal funzionamento di un servizio di trasporto. Verrà infine condotta un’analisi dei fattori che possono influenzare le prestazioni del servizio di trasporto pubblico, così da collocare i dati ottenuti dalle operazioni di rilevamento in un quadro più preciso, capace di sottolineare alcuni elementi di criticità e possibili rapporti di causalità.

Independence in CLP Languages

Studying independence of goals has proven very useful in the context of logic programming. In particular, it has provided a formal basis for powerful automatic parallelization tools, since independence ensures that two goals may be evaluated in parallel while preserving correctness and eciency. We extend the concept of independence to constraint logic programs (CLP) and prove that it also ensures the correctness and eciency of the parallel evaluation of independent goals. Independence for CLP languages is more complex than for logic programming as search space preservation is necessary but no longer sucient for ensuring correctness and eciency. Two additional issues arise. The rst is that the cost of constraint solving may depend upon the order constraints are encountered. The second is the need to handle dynamic scheduling. We clarify these issues by proposing various types of search independence and constraint solver independence, and show how they can be combined to allow dierent optimizations, from parallelism to intelligent backtracking. Sucient conditions for independence which can be evaluated \a priori" at run-time are also proposed. Our study also yields new insights into independence in logic programming languages. In particular, we show that search space preservation is not only a sucient but also a necessary condition for ensuring correctness and eciency of parallel execution.

Abstract specialization and its applications

The aim of program specialization is to optimize programs by exploiting certain knowledge about the context in which the program will execute. There exist many program manipulation techniques which allow specializing the program in different ways. Among them, one of the best known techniques is partial evaluation, often referred to simply as program specialization, which optimizes programs by specializing them for (partially) known input data. In this work we describe abstract specialization, a technique whose main features are: (1) specialization is performed with respect to "abstract" valúes rather than "concrete" ones, and (2) abstract interpretation rather than standard interpretation of the program is used in order to propágate information about execution states. The concept of abstract specialization is at the heart of the specialization system in CiaoPP, the Ciao system preprocessor. In this paper we present a unifying view of the different specialization techniques used in CiaoPP and discuss their potential applications by means of examples. The applications discussed include program parallelization, optimization of dynamic scheduling (concurreney), and integration of partial evaluation techniques.

Independence and search space preservation in dynamically scheduled constraint logic languages

This paper performs a further generalization of the notion of independence in constraint logic programs to the context of constraint logic programs with dynamic scheduling. The complexity of this new environment made necessary to first formally define the relationship between independence and search space preservation in the context of CLP languages. In particular, we show that search space preservation is, in the context of CLP languages, not only a sufficient but also a necessary condition for ensuring that both the intended solutions and the number of transitions performed do not change. These results are then extended to dynamically scheduled languages and used as the basis for the extension of the concepts of independence. We also propose several a priori sufficient conditions for independence and also give correctness and efficiency results for parallel execution of constraint logic programs based on the proposed notions of independence.

Transformation�based implementation and optimization of programs exploiting the basic Andorra model.

The characteristics of CC and CLP systems are in principle very dierent However a recent trend towards convergence in the implementation techniques for these systems can be observed While CLP and Prolog systems have been incorporating capabilities to deal with userdened suspension and coroutining CC compilers have been trying to coalesce negrained tasks into coarsergrained sequential threads This convergence of techniques opens up the possibility of having a general purpose kernel language and abstract machine to serve as a compilation target for a variety of userlevel languages We propose a transformation technique directed towards such an objective In particular we report on techniques to support the Andorra computational model essentially emulating the AndorraI system via program transformation into a sequential language with delay primitives The system is automatic comprising an optional program analyzer and a basic transformer to the kernel language It turns out that a simple parallel CLP or Prolog system with dynamic scheduling is sucient as a kernel language for this purpose The preliminary results are quite encouraging performance of the resulting system is comparable to the current AndorraI implementation.

Minimizing total tardiness in a stochastic single machine scheduling problem using approximate dynamic programming

This paper addresses the non-preemptive single machine scheduling problem to minimize total tardiness. We are interested in the online version of this problem, where orders arrive at the system at random times. Jobs have to be scheduled without knowledge of what jobs will come afterwards. The processing times and the due dates become known when the order is placed. The order release date occurs only at the beginning of periodic intervals. A customized approximate dynamic programming method is introduced for this problem. The authors also present numerical experiments that assess the reliability of the new approach and show that it performs better than a myopic policy.