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

Abstract

This paper proposes a new meta-heuristic optimization algorithm, namely Mud Ring Algorithm (MRA) that mimics the mud ring feeding behaviour of bottlenose dolphins in the Atlantic coast of Florida. The inspiration of MRA is mainly based on the foraging behaviour of bottlenose dolphins and their mud ring feeding strategy. This strategy is applied by dolphins to trap fish via creating a plume by a single dolphin moving his tail swiftly in the sand and swims around the group of fish. The fishes become disoriented and jump over the surface only to find the waiting mouths of dolphins. MRA optimization algorithm mathematically simulates this feeding strategy and proves its optimization effectiveness through a comprehensive comparison with other meta-heuristic algorithms. Twenty-nine benchmark functions and four commonly used benchmark engineering challenges are used in the comparison. The statistical comparisons and results prove that the proposed MRA has the superiority in dealing with these optimization problems and can obtain the best solutions than other meta-heuristic optimizers.

Keywords

• Optimization algorithm
• meta-heuristic
• nature-inspired algorithms
• swarm intelligence
• 3-bar truss design challenge
• tension/compression spring design challenge