A novel Bio-inspired algorithm based on the foraging behaviour of the Bottlenose dolphin

Abstract

Nature has various biological activities which has simulated the development of many elegant algorithms for problem-solving since it exhibits extremely heterogeneous and captivating phenomenon. The bio-inspired tactics have several mesmeric features and choices compared to conventional optimization solvers. Genetic Algorithm (GA)are adaptive heuristic search algorithm based on the evolutionary ideas of natural selection and has significant benefits over more typical search of optimization techniques. Self-organization technique automates the selection of appropriate parameter values of GA during execution without the user's intervention. GA explores the multi-parameter space of solution and in each iterative step; chromosomes are altered. To blend self-organization and GA, it is essential to understand its various aspects clearly. In GA, the selection of appropriate parameters is difficult, reducing run time and avoiding premature convergence is difficult. In this paper, a new Bio-inspired optimization algorithm has been proposed based on the foraging behaviour of the Bottlenose dolphin. Oneofthe famous combinatorial hard problems of Traveling Salesman Problem (TSP) is being chosen as thetest bed.

Mud Ring Algorithm: A New Meta-Heuristic Optimization Algorithm for Solving Mathematical and Engineering Challenges

“…Bottlenose dolphins (Tursiops truncates) are one of 76 marine mammals and cetacean types. They can dive around 260 m down the surface of the ocean [17]. Common bottlenose dolphins can often be found swimming behind trawlers in various areas around the world to search for food.…”

“…Dolphins can also generate a large form of whistles such as signature whistles which are individually specified to communicate location, identity, and probably emotional state. But through social interactions, burst-pulses sounds are generated [17], [18].…”