Most of the engineering design problems are intrinsically complex and difficult to solve, because of diverse solution search space, complex functions, continuous and discrete nature of decision variables, multiple objectives and hard constraints. Swarm intelligence (SI) algorithms are becoming popular in dealing with these kind of complexities. The SI algorithms being population based random search techniques, use heuristics inspired from nature to enable effective exploration of optimal solutions to complex engineering problems. The SI algorithms derived based on principles of co-operative group intelligence and collective behavior of self-organized systems. This chapter presents key principles of multi-optimization, and swarm optimization for solving multi-objective engineering design problems with illustration through few examples.
Multi-objective multicast routing optimization in Cognitive Radio Networks