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S. Kundu, "A Multicriteria Genetic Algorithm to Solve Optimization Problems in Structural Engineering Design", in B. Kumar, (Editor), "Information Processing in Civil and Structural Engineering Design", Civil-Comp Press, Edinburgh, UK, pp 225-233, 1996. doi:10.4203/ccp.37.8.4

Abstract

A Genetic Algorithm (GA) based solution of multicriteria optimization problems in structural engineering design is presented. Design of structural systems is considered as feedback search procedure, where a new solution is assigned some fitness value for the GA, by a reference to the Pareto optimal solutions achieved in the previous function evaluations. The Pareto frontier is shown to move towards the globally optimal region of the feasible solution set of a constrained structural design problem, with the progress of the genetic algorithm generations. The method to analyze multiple criteria by using a GA, is explained in detail. Simulation of a numerical structural control system design example is presented to demonstrate the effectiveness of such an approach.

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Front Page Browse CCP CSETS CTR IJRT Other Authors Search Purchase Guide FAQ Contact us	Civil-Comp Proceedings ISSN 1759-3433 CCP: 37 INFORMATION PROCESSING IN CIVIL AND STRUCTURAL ENGINEERING DESIGN Edited by: B. Kumar Paper VIII.4 A Multicriteria Genetic Algorithm to Solve Optimization Problems in Structural Engineering Design S. Kundu Department of Human and Mechanical Systems Engineering, Kanazawa University, Kanazawa, Japan doi:10.4203/ccp.37.8.4 purchase the full-text of this paper Full Bibliographic Reference for this paper S. Kundu, "A Multicriteria Genetic Algorithm to Solve Optimization Problems in Structural Engineering Design", in B. Kumar, (Editor), "Information Processing in Civil and Structural Engineering Design", Civil-Comp Press, Edinburgh, UK, pp 225-233, 1996. doi:10.4203/ccp.37.8.4 Abstract A Genetic Algorithm (GA) based solution of multicriteria optimization problems in structural engineering design is presented. Design of structural systems is considered as feedback search procedure, where a new solution is assigned some fitness value for the GA, by a reference to the Pareto optimal solutions achieved in the previous function evaluations. The Pareto frontier is shown to move towards the globally optimal region of the feasible solution set of a constrained structural design problem, with the progress of the genetic algorithm generations. The method to analyze multiple criteria by using a GA, is explained in detail. Simulation of a numerical structural control system design example is presented to demonstrate the effectiveness of such an approach. purchase the full-text of this paper (price £20) go to the previous paper go to the next paper return to the table of contents return to the book description purchase this book (price £75 +P&P)
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