Optimal Design of Functionally Graded Steels Using Multi-objective Ant Lion Optimizer

This paper has been devoted to finding optimal construction of advanced functionally graded steels (FGSs) in order to achieve the best compromise between strength and ductility. FGSs have been recently produced via diffusion of the alloying elements during electroslag remelting, which results in a variety of multiphase composites containing ferrite, bainite, martensite, and austenite. Due to the correlation enforced between high strength and poor formability for conventional high strength steels, applying a Pareto-based multi-objective optimization technique is inevitable. The tensile strength and the energy absorption capacity of FGS were considered as fitness functions which should be maximized simultaneously. The tensile strength of FGS was related to the tensile behavior of individual phases by means of the rule of mixtures. Also, the total area under the stress–strain curve was evaluated to quantify the energy absorption capacity. It was assumed that the spatial distribution of the constituents in the graded regions of FGS obeys power functions, including parameters that were chosen as decision variables. A multi-objective ant lion optimizer algorithm (MOALO) was extended and implemented to find a set of Pareto optimal solutions for a five-layer FGS. The results highly demonstrate the efficiency of the proposed MOALO algorithm and its applicability for the excellent approximation of the optimal features of FGSs

functionally graded steel, ant lion optimizer, strength-ductility trade-off, rule of mixtures