Abstract
Water Evaporation Optimization (WEO) is a recently developed physics-based metaheuristic algorithm that mimics the well-known rules governing the evaporation process of water molecules from a solid surface with different wettability. In the WEO algorithm, molecules are updated globally and locally respectively in two independent sequential phases: monolayer and droplet evaporation phases. In this study, the computational cost of the WEO is improved through the simultaneous utilizing of both phases. The new formulation is tested on classical discrete optimization problems achieving a significant enhancement in convergence rate compared to the basic WEO.
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