Complex Optimization with Spiking Neural P Systems

Following Part 1 Theoretical aspects of spiking neural P systems, this chapter opens Part 2 Real-life applications of spiking neural P systems of this book. Differing from membrane-inspired evolutionary algorithms, which use a cell-like or tissue-like P system to properly organize evolutionary operators of heuristic approaches, an optimization SNP system was introduced by considering the mechanism that SNP systems are able to generate languages to directly obtain the approximate solutions of complex optimization problems without the aid of evolutionary operators like in the case of membrane-inspired evolutionary algorithms. This chapter focuses on how to develop a novel way to design an optimization SNP system and how to use the optimization SNP system to solve complex optimization problems such as real-life constrained optimization problems. Several variants of optimization SNP systems and their applications in real-life optimization problems are also discussed.