Gaining New Fields of Application for OOP : the Parallel Evolutionary Algorithm Case

Object Oriented Programming (OOP) is continuously gaining new domains of application. We address in this work a study of several important design and implementation issues in one of such new domains: parallel evolutionary algorithms (PEAs). These algorithms are heuristics aimed at performing search, optimization, and machine learning tasks. We will identify the potential and actual advantages of using OOP in such a field of application, as well as we propose a class design for solving complex real-world problems with PEAs. Besides the methodological and practical outcomes, some results showing the efficiency and flexibility of the resulting OOP-PEA systems are offered herein. We conclude that OOP allows quick PEA prototyping, integration of new techniques within the PEA, and easy cooperation with other techniques in parallel, all of this without reducing the efficiency of the resulting PEA.