Hybrid Migrating Birds Optimization Strategy for t-way Test Suite Generation

Abstract Hybrid meta-heuristics algorithms have gained popularity in recent years to solve t-way test suite generation problems due better exploration and exploitation capabilities of the hybridization. This paper presents implementation meta-heuristic search that are Migrating Birds Optimization (MBO) algorithm Genetic Algorithm (GA) hybrid a data strategy. The proposed strategy is called Elitist MBO-GA Strategy (EMBO-GA). Based on published benchmarking results, result these strategies competitive with most existing terms generated size many parameter configurations. In case where this not optimal, resulting sufficiently competitive.