Numerous steam-assisted gravity-drainage (SAGD) optimization studies published in the literature combined numerical simulation with graphical or analytical techniques for design and performance evaluation. Efforts have integrated the simulation exercise with global optimization algorithms. Some studies focused on optimization of cumulative steam/oil ratio (cSOR) in SAGD by altering steam-injection rates, while others focused on optimization of net cumulative energy/oil ratio (cEOR) in solvent-additive SAGD by altering injection pressures and fraction of solvent in the injection stream. Several studies also considered total project net-present-value (NPV) calculation by changing total project area, capital-cost intensities, solvent prices, and risk factors to determine the well spacing and drilling schedule. Optimization techniques commonly used in those studies were scattered search, simulated annealing, and genetic algorithm (GA). However, applications of hybrid GA were rarely found.