An Effective Exploration on Nature Inspired based Meta-Heuristic Algorithms and their Variants for Solving Decision Making Problems

In order to solve complex decision-making problems that were beyond the capability of traditional optimization methods, nature-inspired meta-heuristic algorithms were introduced and became widely used. The algorithms mimic the behavior of living beings, natural phenomena, and animal movements in the search of good solutions. The present paper is an indepth exploration of these algorithms along with their various incarnations, with a particular focus on their application in decision-making. The paper discusses their mechanisms, advantages, and disadvantages, in both the traditional and modern forms. Besides, standard test problems are utilized in the study in order to evaluate these algorithms on the basis of the time taken to reach the solution, the level of accuracy, and the reliability of the solution. The objective is to highlight the areas for future research and to provide assistance to the experts in selecting the most appropriate algorithms for the resolution of the decision-making problems in the real world.