Weevil Damage Optimization Algorithm (WDOA)

Link to the Paper:

• http://www.growingscience.com/jfs/Vol2/jfs_2022_17.pdf

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• Developed by Seyed Muhammad Hossein Mousavi - (Oct 2022)
• Contact : mosavi.a.i.buali@gmail.com

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- Weevils are a type insect with elongated snouts coming from superfamily of Curculionoidea with approximately 97,000 species. Most of them consider pest and cause environmental damages but some kinds like wheat weevil, maize weevil, and boll weevils are famous to cause huge damage on crops, especially cereal grains. This research is proposed a novel swarm-based metaheuristics algorithms called Weevil Damage Optimization Algorithm (WDOA) which mimics weevils’ fly power, snout power, and damage power on crops or agricultural products. The proposed algorithm is tested with 12 benchmark unimodal and multimodal artificial landscapes or optimization test functions.

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This repository provides the implementation of the Weevil Damage Optimization Algorithm (WDOA), a novel swarm-based metaheuristic inspired by weevils' behavior.

Overview

The WDOA mimics the biological traits of weevils, including:

• Fly Power: Movement toward optimal solutions.
• Snout Power: Exploration of better regions.
• Damage Decision Variable (DDV): Adaptive behavior through mutation.

The algorithm has been applied to benchmark functions (e.g., Ackley) and real-world problems, showing robust accuracy and efficiency.

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Features

1. Inspired by Nature: Mimics weevil behavior for optimization.
2. Tested on Standard Benchmarks: Validated using unimodal, multimodal, constrained, and unconstrained functions.
3. Applicable to Real-world Problems:
   • Travelling Salesman Problem (TSP)
   • n-Queens Problem
   • Portfolio Optimization
   • Optimal Inventory Control (OIC)
   • Bin Packing Problem (BPP)

• DOI : 10.5267/j.jfs.2022.10.003

• Cite:

• Mousavi, S., and S. Mirinezhad. "Weevil damage optimization algorithm and its applications." Journal of Future Sustainability 2.4 (2022): 133-144.