aliasgharheidaricom/Hunger-Games-Search-Visions-Conception-Implementation-Deep-Analysis-and-Performance-Shifts

Visit: https://aliasgharheidari.com/HGS.html. HGS optimizer is a population-based method with stochastic switching elements that enrich its main exploratory and exploitative behaviors and flexibility of HGS in dealing with challenging problem landscapes. The algorithm has been compared to LSHADE, SPS_L_SHADE_EIG, LSHADE_cnEpSi, SHADE, SADE, MPEDE, and JDE methods.

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The Hunger Games Search (HGS) is a general-purpose optimization technique that helps researchers and engineers find optimal solutions for complex problems. It takes in problem definitions, including constraints and objectives, and outputs high-quality, stable solutions more efficiently than many existing methods. This is for anyone working in fields like artificial intelligence or machine learning who needs to optimize system parameters or find the best configuration.

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Use this if you need a robust and efficient way to solve challenging constrained or unconstrained optimization problems in your research or application.

Not ideal if you are looking for a highly specialized optimization algorithm tailored to a very specific, niche problem rather than a general-purpose solution.

optimization artificial-intelligence machine-learning engineering-problems algorithm-design
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 4 / 25
Maturity 16 / 25
Community 9 / 25

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MATLAB

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MIT

Last pushed

Aug 09, 2024

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