56 research outputs found
Algorithms for Large Directed Capacitated Arc Routing Problem Instances: Urban Solid Waste Collection Operational Support
No full textWe present some algorithms for Large Directed Capacitated Arc Routing Problem Instances. They can be used for Urban Solid Waste Collection Operational Suppor
A Fully Distributed Lagrangean Solution for a Peer-to-Peer Overlay Network Design Problem
No full textPeer-to-peer (P2P) computing already accounts for a large part of the traffic on the Internet, and it is likely to become as ubiquitous as current client/server architectures in next generation information systems. This paper addresses a central problem of P2P systems: the design of an optimal overlay communication network for a set of processes on the Internet. Such a network defines membership to the P2P group and allows for members to disseminate information within the group. The problem, named the membership overlay problem (MOP), can be formulated as a dynamic optimization problem where classical combinatorial optimization techniques must face the further challenge of time-varying input data. This paper proposes an innovative, fully distributed, and asynchronous subgradient optimization algorithm for the Lagrangean relaxation of the MOP, which can run online in fully decentralized P2P systems, and integrates it with a distributed heuristic that can achieve sound hot-start states for fast response to varying network structures
A Psychogenetic Algorithm For Behavioral Sequence Learning
No full textThis work presents an original algorithmic model of some essential features of psychogenetic theory, as was proposed by J. Piaget. Specifically, we modeled some elements of cognitive structure learning in children from birth to four months of life. We are in fact convinced that the study of well-established cognitive models of human learning can suggest new, interesting approaches to problem so far not satisfactorily solved in the field of machine learning. Further, we discussed the possible parallels between our model and subsymbolic machine learning and neuroscience. The model was implemented and tested in some simple experimental settings, with reference to the task of learning sensorimotor sequences
Car Racing through the Streets of the Web: A High Speed 3D Game over a Fast Synchronization Service
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VERY STRONGLY CONSTRAINED PROBLEMS: AN ANT COLONY OPTIMIZATION APPROACH
No full textAnt Colony Optimization (ACO) is a class of metaheuristic algorithms sharing the common approach of constructing a solution on the basis of information provided both by a standard constructive heuristic and by previously constructed solutions. This paper is composed of three parts. The first on
Change of the organic detritus quality and quantity in disturbed and undisturbed sediments in a closed coastal lagoon
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Method,and corresponding apparatus,for automatic detection of regions of interest in digital images of biological tissue
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