Abstract

This article describes the origin and significant developments associated with the field of meta-heuristics as they relate to global optimization. Meta-heuristics provide a means for approximately solving complex optimization problems. These methods are designed to search for global optima, however, they cannot guarantee that the best solution found after termination criteria are satisfied is indeed and global optimal solution to the problem. Experimental testing of meta-heuristic implementations show that the search strategies embedded in such procedures are capable of finding solutions of high quality to hard problems in industry, business and science.