Biogeography-Based Optimization Evolutionary Algorithm (BBO) with Test Functions

This documentation provides a detailed implementation of the Biogeography-Based Optimization (BBO) evolutionary algorithm along with several test function suites. The algorithm operates through habitat migration and mutation mechanisms inspired by species distribution patterns across geographical regions. To execute the optimization process, simply call BBO(@FunctionName) where the function handle specifies the objective function, for instance BBO(@QuarticDisc) initiates optimization using the Quartic Disc function. The code structure includes key components: habitat initialization with candidate solutions, migration rates calculation based on habitat suitability index, elitism preservation for best solutions, and mutation operators for diversity maintenance. Additional background information about the algorithm's mathematical foundation and practical application cases will be provided to help readers better understand and apply BBO in optimization problems. The implementation supports customizable parameters including population size, maximum iterations, and migration probabilities for different optimization scenarios.