In this work, we present a genetic algorithm framework for the FPGA placement problem. This framework is constructed based on previous proposals in this domain. We implement this f...
Abstract. Quasigroups are a well-known combinatorial design equivalent to more familiar Latin squares. Because all possible elements of a quasigroup occur with equal probability, i...
In this paper, the authors compare a Monte Carlo method and an optimization-based approach using genetic algorithms for sequentially generating space-filling experimental designs....
: Warehouses scheduling is the problem of sequencing requests of products to fulfill several customers’ orders so as to minimize the average time and shipping costs. In this pape...
A multiobjective genetic algorithm for detecting communities in dynamic networks, i.e., networks that evolve over time, is proposed. The approach leverages on the concept of evolu...
We propose a novel, local feature-based face representation method based on twostage subset selection where the first stage finds the informative regions and the second stage ...
This work addresses the problem of finding the adjustable parameters of a learning algorithm using Genetic Algorithms. This problem is also known as the model selection problem. In...
: This paper describes the successful parallel implementation of genetic programming on a network of processing nodes using the transputer architecture. With this approach, researc...
- Genetic algorithms (GAs) search for good solutions to a problem by operations inspired from the natural selection of living beings. Among their many uses, we can count informatio...
In this paper we present a genetic algorithm-based heuristic for solving the set partitioning problem (SPP). The SPP is an important combinatorial optimisation problem used by man...