The quadratic multiple knapsack problem extends the quadratic knapsack problem with K knapsacks, each with its own capacity Ck. A greedy heuristic fills the knapsacks one at a tim...
This work describes a forward-looking approach for the solution of dynamic (time-changing) problems using evolutionary algorithms. The main idea of the proposed method is to combi...
Genetic Algorithm (GA) is known as a potent multiobjective optimization method, and the effectiveness of hybridizing it with local search (LS) has recently been reported in the li...
Semi-supervised classification uses aspects of both unsupervised and supervised learning to improve upon the performance of traditional classification methods. Semi-supervised clu...
Evolutionary Computations in dynamic/uncertain environments have attracted much attention. Studies regarding this research subjects can be classified into four categories: Noise, ...
We present an evolutionary methodology that explores the evolution of network topology when a uniform growth of the network traffic is considered. The network redesign problem is ...
We consider the Bounded Diameter Minimum Spanning Tree problem and describe four neighbourhood searches for it. They are used as local improvement strategies within a variable nei...
In this article, new variation operators for evolutionary multiobjective algorithms (EMOA) are proposed. On the basis of a predator-prey model theoretical considerations as well a...