Wild Goats Algorithm: An Evolutionary Algorithm to Solve the Real-World Optimization Problems

Abstract

Solution of optimization problems is inseparable part of science and engineering. The close dependence of industry applications on science and engineering clarifies need to optimization algorithms for modern industries. In this paper, the proposition of an evolutionary optimization algorithm is presented. The proposed algorithm is inspired from wild goats’ climbing. The living in the groups and cooperation between members of groups are main ideas which have been inspired. Along the procedure of the algorithm, leaders of groups attract group's other members and eventually the leader of the biggest group reaches the highest point of mountain. Besides examining with a number of benchmark functions, the performance of the algorithm is gone through by one of the energy systems’ important problems, which is known as combined heat and power economic dispatch (CHPED) problem. The aim of the CHPED problem is supplying power and heat demand in an economical manner by conventional thermal units, CHP units, and heat-only units. The effect of valve-point and transmission losses is taken into account in order to consider practical CHPED model. The algorithm is tested on three test systems and the results show the ability of the algorithm to converge the optimum values.