The Flood Algorithm (FLA) is a novel meta-heuristic optimization algorithm inspired by the complex movement and flow patterns of water masses during flooding events in river basins. The algorithm mathematically models key phenomena such as water movement, flow rates, soil permeability, and periodic changes in water levels. It operates in two main phases: a regular movement phase where the population of potential solutions moves naturally toward the best solutions, and a flooding phase that introduces random disturbances to increase diversity. New solutions are periodically introduced while weaker ones are removed, mimicking natural water level cycles. The effectiveness of FLA is demonstrated through its application on well-known benchmark optimization problems and engineering design problems. Extensive comparisons with other algorithms on CEC2005 and CEC2014 functions, as well as on 12 constrained engineering problems, confirm its robustness and strength. The source code for FLA is publicly available at <https://www.optim-app.com/projects/fla>.The Flood Algorithm (FLA) is a novel meta-heuristic optimization algorithm inspired by the complex movement and flow patterns of water masses during flooding events in river basins. The algorithm mathematically models key phenomena such as water movement, flow rates, soil permeability, and periodic changes in water levels. It operates in two main phases: a regular movement phase where the population of potential solutions moves naturally toward the best solutions, and a flooding phase that introduces random disturbances to increase diversity. New solutions are periodically introduced while weaker ones are removed, mimicking natural water level cycles. The effectiveness of FLA is demonstrated through its application on well-known benchmark optimization problems and engineering design problems. Extensive comparisons with other algorithms on CEC2005 and CEC2014 functions, as well as on 12 constrained engineering problems, confirm its robustness and strength. The source code for FLA is publicly available at <https://www.optim-app.com/projects/fla>.