Enhanced Invasive Weed Optimization Algorithm Applied to Electromagnetic Optimization

In recent years there has been extensive research on bio-inspired optimization algorithms. Invasive weed optimization (IWO) was recently proposed as a simple but powerful metaheuristic algorithm for real-parameter optimization. This paper proposes an enhanced IWO algorithm (EIWO), which combines the conventional IWO technique with a strategy using exponential distribution and opposition-based learning. Loney’s solenoid benchmark problem is used to examine the effectiveness of the conventional IWO and the proposed EIWO algorithms. Simulation results and comparisons with EIWO demonstrate that the performance of the IWO approach is promising for electromagnetic design optimization.