Balance of Structural Performance Measures

Furuta, Hiroyuki; Kameda, Takahiro; Frangopol, Dan M.

doi:10.1061/40700(2004)3

Cited by 15 publications

(4 citation statements)

References 3 publications

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“…Pareto raking and fitness sharing techniques were adopted and consequently, diversified Pareto optimal solution set was obtained. Miyamoto optimized the optimal maintenance schemes by minimizing the total maintenance cost and maximizing the sum of carrying capacity and durability using genetic algorithm with binary code [15].Furuta maintained infrastructure system by minimizing the life cycle cost, maximizing the service life and maximizing the object safety level simultaneously using genetic algorithm [16]. Min Liu established a multi-objective optimization model of bridge state index, safety index and life cycle maintenance cost and solved it with genetic algorithm [17].…”

Section: Multi-objective Optimization Based-on Genetic Algorithmmentioning

confidence: 99%

“…Decision tree analysis [1], multiple attribute decision making [2][3][4] and maintenance strategy optimization [5][6][7][8][9][10][11][12][13][14][15][16][17][18] are common methods of maintenance and strengthening decision-making for existing bridges. The selection of the optimum maintenance strategy is a challenging task because the number of possible combinations increases exponentially with the number of bridges, the planning period and the number of maintenance strategies.…”

Section: Introductionmentioning

confidence: 99%

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A Review of Genetic Algorithms Applied to Optimizing Maintenance Strategy of Bridges

Bian

Bai

Shi³

2011

AMR

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Abstract:Along with the fast increasing of maintenance demand, the problems associated with maintenance and reinforcement decision-making for deteriorating bridges such as maintenance strategy optimization have been present research focus. The solutions to these problems have inspired a considerable amount of research, one particular area being the application of evolutionary search algorithms such as the genetic algorithm (GA). This paper begins with a brief overview of bridge maintenance strategy optimization followed by a review of the current state of research in applying evolutionary techniques to solving this problem.

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Section: Multi-objective Optimization Based-on Genetic Algorithmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Review of Genetic Algorithms Applied to Optimizing Maintenance Strategy of Bridges

Bian

Bai

Shi³

2011

AMR

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“…To sustain a practical ideal of a healthier bridge transportation system, under the conditions of material aging, structural deterioration, weather and environmental effects, increasing operational demands, need for improvement of existing bridges, quest for modernization of future bridges, drive for higher efficiency and tight financial limitations constitutes a complex professional challenge in engineering and management for transportation agencies. Studies suggest quantitative evaluations of probabilistic satisfactory performance of bridge inventories, to support professional efforts [1][2][3][4][5][6][7]. Comparative analysis of large populations of bridge categories enables more objective decision-making in bridge design, construction, maintenance, renewal and management [8][9][10][11][12][13][14].…”

Section: Introductionmentioning

confidence: 99%

Structural Performances of Bridge Types in the U.S. National Bridge Inventory

Farhey¹

2018

Infrastructures

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This paper demonstrates a comprehensive national network-level analysis to determine the relative deteriorations and operational structural performances of the various types of bridge structural design and/or construction. The study analyzes the entire database of the U.S. National Bridge Inventory for the year 2013 and considers bridge counts along with bridge deck areas that provide more significant results. Analysis of the proportional distribution of structural deficiency reveals issues of deterioration. Considering the structural deficiency, service life cycle and deterioration trends of bridge types over time, the multi-criteria equivalent structural performances incorporate the condition, durability, longevity, rate and pattern performances. The results provide support for more sustainable engineering and management decisions. Stringer/multi beam or girder (type 02) bridges are the most common bridge type, 40.75% by counts and 61.88% by areas. The structural performance of type 02 bridges seems comparable to the average of all bridges, yet they have lower durability and longevity performances, revealing a relative service life cycle vulnerability. The lowest structural performances are orthotropic (type 08) and segmental box girder (type 21) bridges; while their condition performances are rather high, their durability, longevity, rate and pattern performances are essentially low. The slight improvement of structural performance from 2006 to 2013 for most bridge types is not significant over seven years. Also, certain bridge types worsened.

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“…It is desirable to determine an appropriate life-cycle maintenance plan by comparing several solutions for various conditions [4] [5]. A new decision support system is developed here from the viewpoint of multi-objective optimization, in order to provide various solutions needed for the decision-making.…”

Section: Formulation Of Bridge Maintenance Planningmentioning

confidence: 99%

Application of Multi-Objective Genetic Algorithm to Bridge Maintenance

Furuta

Kameda

IFIP International Federation for Information Processing

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In order to establish a rational bridge management program, it is necessary to develop a cost-effective decision-support system for the maintenance of bridges. In this paper, an attempt is made to develop a new multi-objective genetic algorithm for the bridge management system that can provide practical maintenance plans. Several numerical examples are presented to demonstrate the applicability and efficiency of the proposed method.

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Balance of Structural Performance Measures

Cited by 15 publications

References 3 publications

A Review of Genetic Algorithms Applied to Optimizing Maintenance Strategy of Bridges

A Review of Genetic Algorithms Applied to Optimizing Maintenance Strategy of Bridges

Structural Performances of Bridge Types in the U.S. National Bridge Inventory

Application of Multi-Objective Genetic Algorithm to Bridge Maintenance

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