An Efficient Algorithm for Solving Single Variable Optimization Problems

Abstract

Many methods are available for finding x*E Rn which minimizes the real value function f(x), some of which are Fibonacci Search Algorithm, Quadratic Search Algorithm, Convergence Algorithm and Cubic Search Algorithm. In this research work, existing algorithms used in single variable optimization problems are critically reviewed. The performance comparison of these algorithms is also examined. The algorithms are implemented using flowcharts and codes in Turbo-C programming language. These algorithms are subjected to convergence text to ascertain their efficiency. The result of the study shows that the algorithms used in single variable optimization problem such as Fibonacci, Quadratic and Cubic Search Method almost coincident. It is concluded that of the three optimization Algorithms, cubic search is the most effective single variable optimization technique.