jats:titleAbstract</jats:title>jats:pWe propose a two-stage multi-objective optimization framework for full scheme solar cell jats:italicstructure design and characterization</jats:italic>, jats:italiccost minimization</jats:italic> and jats:italicquantum efficiency maximization</jats:italic>. We evaluated structures of 15 different cell designs simulated by varying material types and photodiode doping strategies. At first, non-dominated sorting genetic algorithm II (NSGA-II) produced Pareto-optimal-solutions sets for respective cell designs. Then, on investigating quantum efficiencies of all cell designs produced by NSGA-II, we applied a new jats:italicmulti-objective optimization algorithm II</jats:italic> (OptIA-II) to discover the Pareto fronts of select (three) best cell designs. Our designed OptIA-II algorithm improved the quantum efficiencies of all select cell designs and reduced their fabrication costs. We observed that the cell design comprising an optimally doped zinc-oxide-based transparent conductive oxide (TCO) layer and rough silver back reflector (BR) offered a quantum efficiency (jats:inline-formulajats:alternativesjats:tex-math$$Q_e$$</jats:tex-math><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> mml:msub mml:miQ</mml:mi> mml:mie</mml:mi> </mml:msub> </mml:math></jats:alternatives></jats:inline-formula>) of 0.6031. Overall, this paper provides a jats:italicfull characterization</jats:italic> of cell structure designs. It derives relationship between quantum efficiency, jats:inline-formulajats:alternativesjats:tex-math$$Q_e$$</jats:tex-math><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> mml:msub mml:miQ</mml:mi> mml:mie</mml:mi> </mml:msub> </mml:math></jats:alternatives></jats:inline-formula> of a cell with its TCO layer’s doping methods and TCO and BR layer’s material types. Our solar cells design characterization enables us to perform a cost-benefit analysis of solar cells usage in real-world applications.</jats:p>