-convex set-valued maps with values in .
Paradox in a Non-Linear Capacitated Transportation Problem
Parallel approximation to high multiplicity scheduling problems smooth multi-valued quadratic programming
We consider the parallel approximability of two problems arising from high multiplicity scheduling, namely the unweighted model with variable processing requirements and the weighted model with identical processing requirements. These two problems are known to be modelled by a class of quadratic programs that are efficiently solvable in polynomial time. On the parallel setting, both problems are P-complete and hence cannot be efficiently solved in parallel unless P = NC. To deal with the parallel...
Parallel approximation to high multiplicity scheduling problems VIA smooth multi-valued quadratic programming
We consider the parallel approximability of two problems arising from high multiplicity scheduling, namely the unweighted model with variable processing requirements and the weighted model with identical processing requirements. These two problems are known to be modelled by a class of quadratic programs that are efficiently solvable in polynomial time. On the parallel setting, both problems are P-complete and hence cannot be efficiently solved in parallel unless P = NC. To deal with the parallel...
Parallel dynamic programming algorithms: Multitransputer systems
The present paper discusses real parallel computations. On the basis of a selected group of dynamic programming algorithms, a number of factors affecting the efficiency of parallel computations such as, e.g., the way of distributing tasks, the interconnection structure between particular elements of the parallel system or the way of organizing of interprocessor communication are analyzed. Computations were implemented in the parallel multitransputer SUPER NODE 1000 system using from 5 to 50 transputers....
Parallel genetic algorithms with migration for the hybrid flow shop scheduling problem.
Parallel machine scheduling with uncertain communication delays
This paper is concerned with scheduling when the data are not fully known before the execution. In that case computing a complete schedule off-line with estimated data may lead to poor performances. Some flexibility must be added to the scheduling process. We propose to start from a partial schedule and to postpone the complete scheduling until execution, thus introducing what we call a stabilization scheme. This is applied to the m machine problem with communication delays: in our model an estimation...
Parallel Machine Scheduling with Uncertain Communication Delays
This paper is concerned with scheduling when the data are not fully known before the execution. In that case computing a complete schedule off-line with estimated data may lead to poor performances. Some flexibility must be added to the scheduling process. We propose to start from a partial schedule and to postpone the complete scheduling until execution, thus introducing what we call a stabilization scheme. This is applied to the m machine problem with communication delays: in our model an estimation...
Parallel method of conjugate directions for minimization
Parallel synchronous algorithm for nonlinear fixed point problems.
Parallélisation d'une combinaison des méthodes de Monte-Carlo et quasi-Monte-Carlo et application aux réseaux de files d'attente
Parallélisation d'une Combinaison des Méthodes de Monte-Carlo et Quasi-Monte-Carlo et Application aux Réseaux de Files d'Attente
We propose a parallel algorithm which uses both Monte-Carlo and quasi-Monte-Carlo methods. A detailed analysis of this algorithm, followed by examples, shows that the estimator's efficiency is a linear function of the processor number. As a concrete application example, we evaluate performance measures of a multi-class queueing network in steady state.
Parallelization algorithms for modeling ARM processes.
Parallelization of artificial immune systems using a massive parallel approach via modern GPUs
Parallelization is one of possible approaches for obtaining better results in terms of algorithm performance and overcome the limits of the sequential computation. In this paper, we present a study of parallelization of the opt-aiNet algorithm which comes from Artificial Immune Systems, one part of large family of population based algorithms inspired by nature. The opt-aiNet algorithm is based on an immune network theory which incorporates knowledge about mammalian immune systems in order to create...
Parameter Estimation in Linear Regression Models With Stationary Arma(p,q)-Errors Using Automatic Differentiation
Parameter Identification of a Fed-Batch Cultivation of S. Cerevisiae using Genetic Algorithms
Fermentation processes as objects of modelling and high-quality control are characterized with interdependence and time-varying of process variables that lead to non-linear models with a very complex structure. This is why the conventional optimization methods cannot lead to a satisfied solution. As an alternative, genetic algorithms, like the stochastic global optimization method, can be applied to overcome these limitations. The application of genetic algorithms is a precondition for robustness...
Parametric integer programming
Parametric problem of completely generalized quasi-variational inequalities.
Parametric set-valued vector quasi-equilibrium problems.
Paramétrisation et approximation d'un problème non convexe ; application à un problème de gestion de portefeuille