• Title/Summary/Keyword: computational optimisation

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Optimal sensor placement for mode shapes using improved simulated annealing

  • Tong, K.H.;Bakhary, Norhisham;Kueh, A.B.H.;Yassin, A.Y. Mohd
    • Smart Structures and Systems
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    • v.13 no.3
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    • pp.389-406
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    • 2014
  • Optimal sensor placement techniques play a significant role in enhancing the quality of modal data during the vibration based health monitoring of civil structures, where many degrees of freedom are available despite a limited number of sensors. The literature has shown a shift in the trends for solving such problems, from expansion or elimination approach to the employment of heuristic algorithms. Although these heuristic algorithms are capable of providing a global optimal solution, their greatest drawback is the requirement of high computational effort. Because a highly efficient optimisation method is crucial for better accuracy and wider use, this paper presents an improved simulated annealing (SA) algorithm to solve the sensor placement problem. The algorithm is developed based on the sensor locations' coordinate system to allow for the searching in additional dimensions and to increase SA's random search performance while minimising the computation efforts. The proposed method is tested on a numerical slab model that consists of two hundred sensor location candidates using three types of objective functions; the determinant of the Fisher information matrix (FIM), modal assurance criterion (MAC), and mean square error (MSE) of mode shapes. Detailed study on the effects of the sensor numbers and cooling factors on the performance of the algorithm are also investigated. The results indicate that the proposed method outperforms conventional SA and Genetic Algorithm (GA) in the search for optimal sensor placement.

A Variable Neighbourhood Descent Algorithm for the Redundancy Allocation Problem

  • Liang, Yun-Chia;Wu, Chia-Chuan
    • Industrial Engineering and Management Systems
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    • v.4 no.1
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    • pp.94-101
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    • 2005
  • This paper presents the first known application of a meta-heuristic algorithm, variable neighbourhood descent (VND), to the redundancy allocation problem (RAP). The RAP, a well-known NP-hard problem, has been the subject of much prior work, generally in a restricted form where each subsystem must consist of identical components. The newer meta-heuristic methods overcome this limitation and offer a practical way to solve large instances of the relaxed RAP where different components can be used in parallel. The variable neighbourhood descent method has not yet been used in reliability design, yet it is a method that fits perfectly in those combinatorial problems with potential neighbourhood structures, as in the case of the RAP. A variable neighbourhood descent algorithm for the RAP is developed and tested on a set of well-known benchmark problems from the literature. Results on 33 test problems ranging from less to severely constrained conditions show that the variable neighbourhood descent method provides comparable solution quality at a very moderate computational cost in comparison with the best-known heuristics. Results also indicate that the VND method performs with little variability over random number seeds.

A BIM-based model for constructability assessment of conceptual design

  • Fadoul, Abdelaziz;Tizani, Walid;Koch, Christian
    • Advances in Computational Design
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    • v.3 no.4
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    • pp.367-384
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    • 2018
  • The consideration of constructability issues at the design stage can lead to improved construction performance with smooth project delivery and savings in time and money. Empirical studies demonstrate the value obtained by integrating construction knowledge with the building design process, and its benefits for owners, contractors and designers. However, it is still a challenge to implement the concept into current design practice. There is a need for a decision support tool to aid designers in reviewing their design constructability, deploying current technological tools, such as BIM. Such tools are beneficial at the conceptual design stage when there is a room to improve the design significantly with less incurred cost. This research investigates how current process- and object-oriented models can be used to assess design constructability. It proposes a BIM-based model using embedded information within the design environment to conduct the assessment. The modelling framework is demonstrated in four key parts; namely, the conceptual design model, the constructability assessment model, the assessment process model and the decision-making phase. Each is associated with a set of components and functions that contribute towards the targeted constructability assessment outcomes. The proposed framework is the first to combine a numerical assessment system and a rule-based system, allowing for both quantitative and qualitative approaches. The modelling framework and its implementation through a prototype are described in this paper. It is believed that this framework is the first to enable users to transfer their construction knowledge and experience directly into a design platform linked to BIM models. The assessment criteria can be customised by the users who can reflect their own constructability preferences into various specialised profiles that can be added to the constructability assessment model. It also allows for the integration of the assessment process with the design phase, facilitating the optimisation of constructability performance from the early design stage.