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Abstract The Purpose of this research is the development Direct Search Methods for minimizing the objective function; The Developed Methods reduces the approach time to the minimum through two techniques: 1) by reducing...

Abstract In this research a simulation parallel algorithm for data hiding and data retrieval in gray digital image files were used. A simulation for this algorithm was applied on star network type. The secret image and ...

In this paper we present a study of a parallel Ant Colony System (ACS) for the two-dimensional strip packing problem. In our computational study, we emphasize the in uence of the incorporation of the received information...

In the Laboratory of Research and Development on Computer Science of the National University of La Plata, a face recognition system has been developed. This article describes a series of testings based on parallel proces...

Sequential and parallel evolutionary algorithms (EAs) are developed and evaluated on two hard optimisation problems arising in the field of Telecommunications: designing error correcting codes, and finding optimal placem...

Parallel genetic algorithms, models and implementations, attempts to exploit the intrinsically parallel nature of genetic algorithms. By distributing the total population, these models ref1ects a bebaviour nearer to that...

Determining an optimal schedule to m1mm1ze the completion time of the last job abandoning the system (makespan) become a very difficult problem when there are more than two machines in the flow shop. Due both to its econ...

Ant Colony Optimization algorithms are intrinsically distributed algorithms where independent agents are in charge of building solutions. Stigmergy or indirect communication is the way in which each agent learns from the...

In several applications, the trajectory of an entity, a feature or an object has to be tracked over a sequence of image frames. When the processing is to be performed in real time, there are important constraints leading...

The growing importance and interest in parallel processing within Computer Sciences are undeniable, and thus make it one of the more influencing areas of this discipline. Several reasons support this fact, such as the in...

Evolutionary computation (EC) has been recently recognized as a research field, which studies a new type of algorithms: Evolutionary Algorithms (EAs). These algorithms process populations of solutions as opposed to most ...

Migration of individuals allows a fruitful interaction between subpopulations in the island model, a well known distributed approach for evolutionary computing, where separate subpopulations evolve in parallel. This mode...

Identical parallel machines problems (Pm) involve task assignments to the system's resources (a machine bank in parallel). The basic model consists of m machines and n tasks. The tasks are assigned according to the avail...

Parallel machine scheduling, also known as parallel task scheduling, involves the assignment of multiple tasks onto the system architecture’s processing components (a bank of machines in parallel). A basic model invol...

This work summarizes results when facing the problem of allocating a number of nonidentical tasks in a parallel system. The model assumes that the system consists of a number of identical processors and that only one tas...

Evolutionary computation (EC) has been recently recognized as a research field, which studies a new type of algorithms: Evolutionary Algorithms (EAs). These algorithms process populations of solutions as opposed to most ...

An electromagnetic transient (EMT) simulation framework is developed by integrating the Parallel-in-Time algorithm with a data-oriented Entity–Component–System (ECS) architecture. The proposed method aims t...

A DNA sequence analysis parallelization in large databases using cluster, multi-cluster, and GRID is presented. Achievable speedup, scalability, and overhead introduced by communications are discussed, and the impact of ...

Cellular automata provide an abstract model of parallel com- putation that can be effectively used for modeling and simulation of com- plex phenomena and systems. The design and implementation of parallel programming lan...

Parallel performance optimization is being applied and further improvements are studied for parallel linear algebra on clusters. Several parallelization guidelines have been defined and are being used on single clusters ...

The development of parallel algorithms for an automatic recognition and classification of objects from an industrial line (either production or packaging) is presented. This kind of problem introduces a temporal restrict...

This paper describes two parallel algorithms for the eÆcient processing of relational database transactions and presents a performance analysis of them. These algorithms are built upon the bulk-synchronous parallel mode...

The back-propagation algorithm is one of the most widely used training algorithms for neural networks. The training phase of a multilayer perceptron by using this algorithm can take very long time making neural networks ...

The AMTHA (Automatic Mapping Task on Heterogeneous Architectures) algorithm for task-to-processors assignment and the MPAHA (Model of Parallel Algorithms on Heterogeneous Architectures) model are presented. The use of A...