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Algorithms and Metaheuristics for Combinatorial Matrices

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Abstract

Combinatorial matrices are matrices that satisfy certain combinatorial properties and typically give rise to extremely challenging search problems with thousands of variables. In this chapter we present a survey of some recent algorithms to search for some kinds of combinatorial matrices, with an emphasis to algorithms within the realm of optimization and metaheuristics. It is to be noted that for most kinds of combinatorial matrices there are several known infinite classes in the literature, but these infinite classes do not suffice to cover the entire spectra of possible orders of these matrices, therefore it is necessary to resort to computational and meta-heuristic algorithms.

Keywords

Particle Swarm Optimization Power Spectral Density Binary Sequence Hadamard Matrice Particle Swarm Optimization Variant 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Authors and Affiliations

  1. 1.Department of Physics and Computer ScienceWilfrid Laurier University, WaterlooONCanada

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