This paper introduces a new metaheuristic optimization method based on evolutionary algorithms to solve single-objective engineering optimization problems faster and more efficient. By considering constraints as a new objective function, problems turned to multi objective optimization problems. To avoid regular local optimum, different mutations and crossovers are studied and the best operators due their performances are selected as main operators of algorithm. Moreover, certain infeasible solutions can provide useful information about the direction which lead to best solution, so these infeasible solutions are defined on basic concepts of optimization and uses their feature to guide convergence of algorithm to global optimum. Dynamic interference of mutation and crossover are considered to prevent unnecessary calculation and also a selection strategy for choosing optimal solution is introduced. To verify the performance of the proposed algorithm, some CEC 2006 optimization problems which prevalently used in the literatures, are inspected. After satisfaction of acquired result by proposed algorithm on mathematical problems, four popular engineering optimization problems are solved. Comparison of results obtained by proposed algorithm with other optimization algorithms show that the suggested method has a powerful approach in finding the optimal solutions and exhibits significance accuracy and appropriate convergence in reaching the global optimum.

This paper introduces a new metaheuristic optimization method based on evolutionary algorithms to solve single-objective engineering optimization problems faster and more efficient. By considering constraints as a new objective function, problems turned to multi objective optimization problems. To avoid regular local optimum, different mutations and crossovers are studied and the best operators due their performances are selected as main operators of algorithm. Moreover, certain infeasible solutions can provide useful information about the direction which lead to best solution, so these infeasible solutions are defined on basic concepts of optimization and uses their feature to guide convergence of algorithm to global optimum. Dynamic interference of mutation and crossover are considered to prevent unnecessary calculation and also a selection strategy for choosing optimal solution is introduced. To verify the performance of the proposed algorithm, some CEC 2006 optimization problems which prevalently used in the literatures, are inspected. After satisfaction of acquired result by proposed algorithm on mathematical problems, four popular engineering optimization problems are solved. Comparison of results obtained by proposed algorithm with other optimization algorithms show that the suggested method has a powerful approach in finding the optimal solutions and exhibits significance accuracy and appropriate convergence in reaching the global optimum.

Keywords:## evolutionary algorithm, single objective optimization problem, multi objective optimization algorithm constraint handling, Constraint optimization, civil optimization problem,

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Bibtex | `@araştırma makalesi { tekderg541640, journal = {Teknik Dergi}, issn = {1300-3453}, address = {}, publisher = {TMMOB İnşaat Mühendisleri Odası}, year = {2021}, volume = {32}, pages = {10645 - 10674}, doi = {10.18400/tekderg.541640}, title = {An Effective Improved Multi-objective Evolutionary Algorithm (IMOEA) for Solving Constraint Civil Engineering Optimization Problems}, key = {cite}, author = {Ghohanı Arab, Hamed and Mahallatı Rayenı, Ali and Ghasemı, Mohamad Reza} }` |

APA | Ghohanı Arab, H , Mahallatı Rayenı, A , Ghasemı, M . (2021). An Effective Improved Multi-objective Evolutionary Algorithm (IMOEA) for Solving Constraint Civil Engineering Optimization Problems . Teknik Dergi , 32 (2) , 10645-10674 . DOI: 10.18400/tekderg.541640 |

MLA | Ghohanı Arab, H , Mahallatı Rayenı, A , Ghasemı, M . "An Effective Improved Multi-objective Evolutionary Algorithm (IMOEA) for Solving Constraint Civil Engineering Optimization Problems" . Teknik Dergi 32 (2021 ): 10645-10674 < |

Chicago | Ghohanı Arab, H , Mahallatı Rayenı, A , Ghasemı, M . "An Effective Improved Multi-objective Evolutionary Algorithm (IMOEA) for Solving Constraint Civil Engineering Optimization Problems". Teknik Dergi 32 (2021 ): 10645-10674 |

RIS | TY - JOUR T1 - An Effective Improved Multi-objective Evolutionary Algorithm (IMOEA) for Solving Constraint Civil Engineering Optimization Problems AU - Hamed Ghohanı Arab , Ali Mahallatı Rayenı , Mohamad Reza Ghasemı Y1 - 2021 PY - 2021 N1 - doi: 10.18400/tekderg.541640 DO - 10.18400/tekderg.541640 T2 - Teknik Dergi JF - Journal JO - JOR SP - 10645 EP - 10674 VL - 32 IS - 2 SN - 1300-3453- M3 - doi: 10.18400/tekderg.541640 UR - Y2 - 2019 ER - |

EndNote | %0 Teknik Dergi An Effective Improved Multi-objective Evolutionary Algorithm (IMOEA) for Solving Constraint Civil Engineering Optimization Problems %A Hamed Ghohanı Arab , Ali Mahallatı Rayenı , Mohamad Reza Ghasemı %T An Effective Improved Multi-objective Evolutionary Algorithm (IMOEA) for Solving Constraint Civil Engineering Optimization Problems %D 2021 %J Teknik Dergi %P 1300-3453- %V 32 %N 2 %R doi: 10.18400/tekderg.541640 %U 10.18400/tekderg.541640 |

ISNAD | Ghohanı Arab, Hamed , Mahallatı Rayenı, Ali , Ghasemı, Mohamad Reza . "An Effective Improved Multi-objective Evolutionary Algorithm (IMOEA) for Solving Constraint Civil Engineering Optimization Problems". Teknik Dergi 32 / 2 (Mart 2021): 10645-10674 . |

AMA | Ghohanı Arab H , Mahallatı Rayenı A , Ghasemı M . An Effective Improved Multi-objective Evolutionary Algorithm (IMOEA) for Solving Constraint Civil Engineering Optimization Problems. Teknik Dergi. 2021; 32(2): 10645-10674. |

Vancouver | Ghohanı Arab H , Mahallatı Rayenı A , Ghasemı M . An Effective Improved Multi-objective Evolutionary Algorithm (IMOEA) for Solving Constraint Civil Engineering Optimization Problems. Teknik Dergi. 2021; 32(2): 10645-10674. |

IEEE | H. Ghohanı Arab , A. Mahallatı Rayenı ve M. Ghasemı , "An Effective Improved Multi-objective Evolutionary Algorithm (IMOEA) for Solving Constraint Civil Engineering Optimization Problems", Teknik Dergi, c. 32, sayı. 2, ss. 10645-10674, Mar. 2021, doi:10.18400/tekderg.541640 |

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