2011
DOI: 10.1007/s00707-011-0564-1
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Performance-based multi-objective optimization of large steel structures

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Cited by 94 publications
(15 citation statements)
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“…Hinow and Mevissen [9] use genetic algorithm to optimize LCC of a substation, improving the maintenance activities. In Kaveh et al [10] genetic algorithms, exactly NSGA-2, is used to perform a multi-objective optimization of LCC and initial costs of large steel structures. Here it is possible to see the strong trade-off between initial costs and life cycle costs.…”
Section: State Of the Artmentioning
confidence: 99%
“…Hinow and Mevissen [9] use genetic algorithm to optimize LCC of a substation, improving the maintenance activities. In Kaveh et al [10] genetic algorithms, exactly NSGA-2, is used to perform a multi-objective optimization of LCC and initial costs of large steel structures. Here it is possible to see the strong trade-off between initial costs and life cycle costs.…”
Section: State Of the Artmentioning
confidence: 99%
“…A more comprehensive decision making study on design alternatives may be achieved by the use of multi-objective optimization procedures and resultant Pareto optimal design alternatives. Multi-objective optimum seismic design has been utilized by various researchers [13][14][15][16]. Life cycle and initial costs are introduced as optimization objectives in most of these researches.…”
Section: Introductionmentioning
confidence: 99%
“…Liu et al [18] used a robust performance based design approach for a multi-objective optimization using genetic algorithm subjected to uncertainties and provided a set of Pareto optimal designs. Commonly, evolutionary algorithms are employed to solve structural optimization problems owing to their complexity [16]. In this study, NSGA-II [19] is used for solving the defined multi-objective optimization problem.…”
Section: Introductionmentioning
confidence: 99%
“…Many realistic problems contain simultaneous optimization of several objectives in which these objectives may conflict with each other and with other nonlinear constraints, if exist [1][2][3][4][5][6][7]. These types of problems are known as Multi-Objective Problems (MOPs).…”
Section: Introductionmentioning
confidence: 99%