Multiobjective forensic-based investigation algorithm for solving structural design problems

• Published in: Automation in construction 2022-02, Vol.134, p.104084, Article 104084
• Main Authors: Chou, Jui-Sheng, Truong, Dinh-Nhat
• Format: Article
• Language: English
• Subjects: Computer-aided design; Crime; Criminal investigations; Design engineering; Domes; Evolutionary algorithms; Genetic algorithms; Heuristic methods; Metaheuristics; Multi-objective FBI algorithm; Multiple objective analysis; Multiple objective optimization; Optimization; Pareto optimization; Pareto optimum; Pareto-optimal fronts; Particle swarm optimization; Police; Structural design; Structural design optimization; Structural engineering; Trusses
• ISSN: 0926-5805; 1872-7891
• DOI: 10.1016/j.autcon.2021.104084

A multi-objective forensic-based investigation (MOFBI) algorithm is developed to solve engineering optimization problems with multiple objectives. In the proposed algorithm, a chaotic map is used to initialize the population; Lévy flight, two elite populations, and a fixed-size archive are used to operate the motions of investigators and police officers in the criminal search and arrest procedures, and a control time mechanism is used to balance exploration and exploitation in MOFBI to obtain Pareto-optimal solutions in multi-objective search spaces. Eight well-known multiple-objective metaheuristic optimization algorithms - the multi-objective ant lion optimizer (MOALO), the multi-objective dragonfly algorithm (MODA), the multi-objective evolutionary algorithm based on decomposition (MOEA/D), the multi-objective grey wolf optimizer (MOGWO), the multi-objective particle swarm optimization (MOPSO), the fast and elitist multi-objective genetic algorithm (NSGA-II), pareto envelope-based selection algorithm II (PESA-II) and the strength pareto evolutionary algorithm II (SPEA-II) - are compared to MOFBI with respect to performance in solving 24 multi-objective mathematical benchmark problems (CEC-2020 functions). The Wilcoxon rank sum test of hypervolume index, generational distance and spacing reveal that MOFBI can find more accurate approximations of Pareto-optimal fronts than the other algorithms. MOFBI is then used to solve five structural engineering design problems, including the 10-bar truss, the 72-bar truss, the 56-bar dome, the 120-bar dome and the 582-bar tower. The results obtained using MOFBI and comparison thereof with previously obtained results indicate the effectiveness of MOFBI in finding the best Pareto-optimal solutions. Therefore, MOFBI is a powerful computer-aided tool for solving multi-objective optimization problems. •A multi-objective forensic-based investigation (MOFBI) algorithm is developed for solving multiple-objective problems.•The MOFBI was compared with well-known metaheuristic optimization algorithms by testing on mathematical functions.•Five structural design problems were efficiently solved using MOFBI.•The analytical results demonstrate the robustness of MOFBI in finding the best Pareto-optimal fronts.