-convex set-valued maps with values in .
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 method of conjugate directions for minimization
Parallel synchronous algorithm for nonlinear fixed point problems.
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
Parametrization in nonserial dynamic programming
Partially clairvoyant scheduling for aggregate constraints.
Partially observable Markov decision processes with partially observable random discount factors
This paper deals with a class of partially observable discounted Markov decision processes defined on Borel state and action spaces, under unbounded one-stage cost. The discount rate is a stochastic process evolving according to a difference equation, which is also assumed to be partially observable. Introducing a suitable control model and filtering processes, we prove the existence of optimal control policies. In addition, we illustrate our results in a class of GI/GI/1 queueing systems where...
Partially observable queueing systems with controlled service rates under a discounted optimality criterion
We are concerned with a class of queueing systems with controlled service rates, in which the waiting times are only observed when they take zero value. Applying a suitable filtering process, we show the existence of optimal control policies under a discounted optimality criterion.
Particle swarm optimization with various inertia weight variants for optimal power flow solution.
Partitioned Variable Metric Updates for Large Structured Optimization Problems.