Metaheuristic Masterclass Part 1 : Whale Optimization Technique


The Whale Optimization Technique (WOA) is a nature-inspired meta-heuristic optimization algorithm that mimics the unique hunting behavior of humpback whales, specifically their bubble-net feeding strategy. The algorithm was proposed in 2016 and is widely used for solving complex optimization problems across diverse domains.​

How WOA Works

WOA simulates three primary behaviors:

  • Encircling Prey: Search agents (whale representations) attempt to position themselves around the best solution found so far, mimicking whales surrounding prey.​

  • Bubble-Net Attacking (Exploitation): Agents update their positions in a spiral pattern towards the optimal solution, representing the bubble-net maneuver whales use to trap prey, which helps intensify the search around promising solutions.​

  • Search for Prey (Exploration): The algorithm maintains diversity by allowing agents to follow randomly selected solutions, exploring different regions of the search space.​

WOA balances exploration and exploitation via adaptive parameters, ensuring an effective and robust search for optimal solutions in single- and multi-objective problems.


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