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Metaheuristic Optimization in Seismic Structural Design and Inspection Scheduling of Buildings

Metaheuristic Optimization in Seismic Structural Design and Inspection Scheduling of Buildings
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Author(s): Chara Ch. Mitropoulou (Institute of Structural Analysis and Seismic Research, National Technical University Athens, Greece), Vagelis Plevris (School of Pedagogical and Technological Education (ASPETE), Greece)and Nikos D. Lagaros (Institute of Structural Analysis and Seismic Research, National Technical University Athens, Greece)
Copyright: 2013
Pages: 21
Source title: Data Mining: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-4666-2455-9.ch109

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Abstract

Optimization is a field where extensive research has been conducted over the last decades. Many types of problems have been addressed, and many types of algorithms have been developed, while their range of applications is continuously growing. The chapter is divided into two parts; in the first part, the life-cycle cost analysis is used as an assessment tool for designs obtained by means of prescriptive and performance-based optimum design methodologies. The prescriptive designs are obtained through a single-objective formulation, where the initial construction cost is the objective to be minimized, while the performance-based designs are obtained through a two-objective formulation where the life-cycle cost is considered as an additional objective also to be minimized. In the second part of the chapter, the problem of inspection of structures and routing of the inspection crews following an earthquake in densely populated metropolitan areas is studied. A model is proposed and a decision support system is developed to aid local authorities in optimally assigning inspectors to critical infrastructures. A combined particle swarm – ant colony optimization based framework is implemented, which proves to be an instance of a successful application of the philosophy of bounded rationality and decentralized decision-making for solving global optimization problems.

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