Multiobjective forensic-based investigation algorithm for solving structural design problems

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 o...

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Published in:	Automation in construction Vol. 134; p. 104084
Main Authors:	Chou, Jui-Sheng, Truong, Dinh-Nhat
Format:	Journal Article
Language:	English
Published:	Amsterdam Elsevier B.V 01.02.2022 Elsevier BV
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 Multi-objective FBI algorithm Structural design optimization Computer-aided design Pareto-optimal fronts Multiple objective optimization Metaheuristics
ISSN:	0926-5805, 1872-7891
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Abstract	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.
AbstractList	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 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.
ArticleNumber	104084
Author	Truong, Dinh-Nhat Chou, Jui-Sheng
Author_xml	– sequence: 1 givenname: Jui-Sheng surname: Chou fullname: Chou, Jui-Sheng email: jschou@mail.ntust.edu.tw organization: National Taiwan University of Science and Technology, Taipei, Taiwan – sequence: 2 givenname: Dinh-Nhat surname: Truong fullname: Truong, Dinh-Nhat email: D10605806@mail.ntust.edu.tw, nhat.truongdinh@uah.edu.vn organization: University of Architecture Ho Chi Minh City, Ho Chi Minh City, Viet Nam
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Snippet	A multi-objective forensic-based investigation (MOFBI) algorithm is developed to solve engineering optimization problems with multiple objectives. In the...
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SubjectTerms	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
Title	Multiobjective forensic-based investigation algorithm for solving structural design problems
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