Although it is widely acknowledged that multi-way dataaow constraints make it easier to specify certain relationships in interactive applications, concerns about their eeciency have impeded their acceptance. Some of the local propagation algorithms that solve these constraints are polynomial, others (such as SkyBlue) are exponential. In fact, every system handles a speciic problem and the innue...

The aim of this work is to deene a paradigm which supports the routing of demands across distinct network domains. The distributed nature of this problem (the network resources are spatially distributed and distinct domains can be heterogeneous environments) and the constraints imposed by the environment suggest the use of distributed problem solving methodologies and multi-agent technology. In...

Multi-objective optimization problems are considered in the field of non-steady metal forming processes, such as forging or wire drawing. The Pareto optimal front of the problem solution set is calculated by a Genetic Algorithm. In order to reduce the inherent computational cost of such algorithms, a surrogate model is developed and replaces the exact the function simulations. It is based on th...

This paper focuses on parameter search for multi-agent based models using evolutionary algorithms. Large numbers and variable dimensions of parameters require a search method which can efficiently handle a high dimensional search space. We are proposing the use of complexification as it emulates the natural way of evolution by starting with a small constrained search space and expanding it as t...

Computing applications such as metaheuristics-based optimization can greatly benefit from multi-core architectures available on modern supercomputers. In this paper, we describe an easy and efficient way to implement certain population-based algorithms (in the discussed case, multi-agent computing system) on such runtime environments. Our solution is based on an Erlang software library which im...

Series of measurements should be planned carefully in order to reduce the costs and to allow an efficient execution at measuring devices. For this planning process, we present a multi-step optimization method using genetic algorithms. As a concrete application, we arrange a set of Design of Experiment measuring points appearing during the calibration of combustion engines in an optimal way. Key...

it is shown in [1] that the optimal downlink radio resource allocation for non-realtime traffic in cellular cdma/tdma networks can be mapped to a multi-dimensional multiple-choice knapsack problem (mmkp) which is np-hard. in this correspondence we propose a heuristic algorithm with polynomial time complexity for this problem. numerical results indicate significant computational performance impr...

The aim of this work is to deene a paradigm which supports the routing of service demands across distinct network domains. The distributed nature of this problem (i.e., network resources are spatially distributed, and distinct domains can contain heterogeneous components), and the constraints imposed by the environment suggest the use of distributed problem solving techniques and multi-agent te...

We have examined the convergence behavior of the LSCMA in some simple environments. Algorithms such as Multi¬ Target CMA, Multistage CMA, and Iterative Least Squares with Projection can be used for this purpose. The results presented here can form a basis for analysis of these multi-signal extraction techniques. Clearly, the variance and distribution of output SINR obtained with the LSCMA is al...