Eagle Strategy Using L\'evy Walk and Firefly Algorithms For Stochastic Optimization

TL;DR

This paper introduces Eagle Strategy, a hybrid two-stage optimization method combining Le9vy walk and firefly algorithms, demonstrating high efficiency in solving complex stochastic optimization problems.

Contribution

It presents a novel hybrid approach that integrates Le9vy walk and firefly algorithms for improved stochastic optimization performance.

Findings

Eagle Strategy outperforms traditional methods in stochastic problems.

Numerical results confirm high efficiency of the hybrid approach.

The method is applicable to various practical optimization scenarios.

Abstract

Most global optimization problems are nonlinear and thus difficult to solve, and they become even more challenging when uncertainties are present in objective functions and constraints. This paper provides a new two-stage hybrid search method, called Eagle Strategy, for stochastic optimization. This strategy intends to combine the random search using L\'evy walk with the firefly algorithm in an iterative manner. Numerical studies and results suggest that the proposed Eagle Strategy is very efficient for stochastic optimization. Finally practical implications and potential topics for further research will be discussed.