Random Walk‐Based GOOSE Algorithm for Solving Engineering Structural Design Problems

Engineering Reports, Journal Year: 2025, Volume and Issue: 7(5)

Published: April 30, 2025

ABSTRACT The proposed Random Walk‐based Improved GOOSE (IGOOSE) search algorithm is a novel population‐based meta‐heuristic inspired by the collective movement patterns of geese and stochastic nature random walks. This includes inherent balance between exploration exploitation integrating walk behavior with local strategies. In this paper, IGOOSE has been rigorously tested across 23 benchmark functions where 13 benchmarks are varying dimensions (10, 30, 50, 100 dimensions). These provide diverse range optimization landscapes, enabling comprehensive evaluation performance under different problem complexities. various parameters such as convergence speed, magnitude solution, robustness for dimensions. Further, applied to optimize eight distinct engineering problems, showcasing its versatility effectiveness in real‐world scenarios. results these evaluations highlight competitive tool, offering promising both standard complex structural problems. Its ability effectively, combined deal positions valuable tool.

Language: Английский

Stochastic Shaking Algorithm: A New Swarm-Based Metaheuristic and Its Implementation in Economic Load Dispatch Problem

International journal of intelligent engineering and systems, Journal Year: 2024, Volume and Issue: 17(3), P. 276 - 289

Published: May 3, 2024

This paper introduces a novel metaheuristic named the stochastic shaking algorithm (SSA), which is rooted in swarm intelligence principles.The innovation lies its unique utilization of iteration for selecting references during guided searches through approach.The optimization process involves two sequential steps: primary reference first step finest member, while second step, it mean all finer members plus one.This then combined with randomly chosen solution within space, serving as secondary reference.SSA undergoes evaluation contexts.The assessing performance using set 23 classic functions theoretical use case.The tackling economic load dispatch problem (ELD), practical case featuring system 13 generators various energy resources.The study compares SSA against five other metaheuristics-One to One Based Optimization (OOBO), Kookaburra Algorithm (KOA), Language Education (LEO), Total Interaction (TIA), and Walrus (WaOA).Results indicate SSA's superiority over OOBO, KOA, LEO, TIA, WaOA 21, 13, 11, 16, 14 out functions, respectively.Additionally, reveals intense competition among six metaheuristics.

Language: Английский