Phototropic algorithm for global optimisation problems

Abstract

Problem solving and decision-making have a vital role to play in both technical and non-technical fields. Some decisions are simple while others require more effort and time to solve. This article introduces a new problem solving technique called Phototropic optimization algorithm, inspired from the optimised growth pattern in plants. It has been observed that the stem tips of a plant always grow towards sunlight. In this algorithm, the underlying hormonal mechanism of phototropism is emulated to solve computational problems. This phenomenon has indicated strong prospects of algorithmic efficiency and invites further research into prospective computational applications. Phototropic algorithm is developed as an optimization technique to solve real time application such as shortest path finding problems, travelling salesman problem, finding congestion in a network or any similar problem seen around. A prototype on finding the minimal distance between any two nodes in the physical network is modelled here. The asymptotic time complexity analysis shows the algorithm routes packages in O (n log n). Comparison with the traditional algorithms gives sufficient evidence for the efficiency of this proposal. This can be implemented over Software Defined Networks (SDN) for increasing system capabilities in route analytics and functionalities. Extension of this optimization algorithm is useful to solve various real time problems.