The Barter Method: A New Heuristic For Global Optimization And Its Comparison With The Particle Swarm And The Differential Evolution Methods

The objective of this paper is to introduce a new population-based (stochastic) heuristic to search the global optimum of a (continuous) multi-modal function and to assess its performance (on a fairly large number of benchmark functions) vis-à-vis that of two other well-established and very powerful methods, namely, the Particle Swarm (PS) and the Differential Evolution (DE) methods of global optimization. The authors would call this new method the Barter Method of global optimization. For the purpose of brevity, they would not present here any introductory note on the Particle Swarm (or the Modified Repulsive Particle Swarm, MRPS, variant that they have used in this paper) or the DE method.