Journal article
FOM: A framework for metaheuristic optimization
JA Parejo, J Racero, F Guerrero, T Kwok, KA Smith
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics | SPRINGER-VERLAG BERLIN | Published : 2003
Abstract
Most metaheuristic approaches for discrete optimization are usually implemented from scratch. In this paper, we introduce and discuss FOM, an object-oriented framework for metaheuristic optimization to be used as a general tool for the development and the implementation of metaheuristic algorithms. The basic idea behind the framework is to separate the problem side from the metaheuristic algorithms, allowing this to reuse different metaheuristic components in different problems. In addition to describing the design and functionality of the framework, we apply it to illustrative examples. Finally, we present our conclusions and discuss futures developments. © Springer-Verlag Berlin Heidelberg..
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