Constrained multi-objective optimization algorithms: Review and comparison with application in reinforced concrete structures - Afshari, Hamid; Hare, Warren; Tesfamariam, Solomon (Applied soft computing, 2019)
Engineering design problems are often multi-objective in nature, which means trade-offs are required between conflicting objectives. In this study, we examine the multi-objective algorithms for the optimal design of reinforced concrete structures. We begin with a review of multi-objective optimization approaches in general and then present a more focused review on multi-objective optimization of reinforced concrete structures. We note that the existing literature uses metaheuristic algorithms as the most common approaches to solve the multi-objective optimization problems. Other efficient approaches, such as derivative-free optimization and gradient-based methods, are often ignored in structural engineering discipline. This paper presents a multi-objective model for the optimal design of reinforced concrete beams where the optimal solution is interested in trade-off between cost and deflection. We then examine the efficiency of six established multi-objective optimization algorithms, including one method based on purely random point selection, on the design problem. Ranking and consistency of the result reveals a derivative-free optimization algorithm as the most efficient one. •Multi-objective optimization (MOO) approaches in general and in Reinforced Concrete (RC) structures are reviewed.•A novel multi-objective model is developed for the optimal design of RC beams.•A set of algorithms are examined and compared through numerical testing.•This paper enlightens the merits of advanced MOO methods in structural engineering problems.