ArticleSensors (Basel, Switzerland)2022
An Improved Grey Wolf Optimization with Multi-Strategy Ensemble for Robot Path Planning.
Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Hybrid optimization algorithm for solving path planning problems based on grey wolf optimization algorithm.Scientific reports · 2026Article
- Metaheuristic-Driven Ensemble Learning for Robust Fracture Energy Prediction in FDM-Fabricated PLA Components.Polymers · 2026Article
- Hybrid Clustering-Enhanced Brain Storm Optimization Algorithm for Efficient Multi-Robot Path Planning.Biomimetics (Basel, Switzerland) · 2025Article
- Optimal distributed generation placement and sizing using modified grey wolf optimization and ETAP for power system performance enhancement and protection adaptation.Scientific reports · 2025Article
- Article
- GWO-Based Joint Optimization of Millimeter-Wave System and Multilayer Perceptron for Archaeological Application.Sensors (Basel, Switzerland) · 2024Article
- Non-Standard Map Robot Path Planning Approach Based on Ant Colony Algorithms.Sensors (Basel, Switzerland) · 2023Article
- Temperature Compensation of Wind Tunnel Balance Signal Detection System Based on IGWO-ELM.Sensors (Basel, Switzerland) · 2023Article
- Bearing Fault-Detection Method Based on Improved Grey Wolf Algorithm to Optimize Parameters of Multistable Stochastic Resonance.Sensors (Basel, Switzerland) · 2023Article
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Authors and funding
6 authors.
Funding
Abstract
Grey wolf optimization (GWO) is a meta-heuristic algorithm inspired by the hierarchy and hunting behavior of grey wolves. GWO has the superiorities of simpler concept and fewer adjustment parameters, and has been widely used in different fields. However, there are some disadvantages in avoiding prematurity and falling into local optimum. This paper presents an improved grey wolf optimization (IGWO) to ameliorate these drawbacks. Firstly, a modified position update mechanism for pursuing high quality solutions is developed. By designing an ameliorative position update formula, a proper balance between the exploration and exploitation is achieved. Moreover, the leadership hierarchy is strengthened by proposing adaptive weights of
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