ABSTRACT
This chapter investigates the spiral phenomena in nature and attempts to explain and describe the features mathematically. The search behavior in meta-heuristic algorithms is generated by interaction, which enables achieving an effective and global search. In general, the spiral dynamics optimization (SpDO)-based optimization algorithms has fewer parameters compared to other meta-heuristic algorithms. The chapter reviews different spirals and their mathematical descriptions. A common feature of logarithmic spiral is that it can realize an effective search strategy in meta-heuristics and construct a new optimization algorithm based on a discrete model of logarithmic spiral. Nasir proposed the hybridization between the spiral dynamics (SpD) algorithm and bacterial chemotaxis from bacterial foraging algorithm (BFA) for global optimization and developed the hybrid spiral-dynamics bacterial-chemotaxis (HSDBC) optimization algorithm. He proposed four adaptive SpDO algorithms: linear adaptive SpDO, quadratic adaptive SpDO, exponential adaptive SpDO and fuzzy adaptive SpDO. Nasir also applied the hybrid spiral-dynamics bacterial-foraging (HSDBF) algorithm for global optimization with applications to control design.
