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More About This Title Cost Optimization of Structures
In this groundbreaking book the authors present novel computational models for cost optimization of large scale, realistic structures, subjected to the actual constraints of commonly used design codes.
As the first book on the subject this book:
- Contains detailed step-by-step algorithms
- Focuses on novel computing techniques such as genetic algorithms, fuzzy logic, and parallel computing
- Covers both Allowable Stress Design (ASD) and Load and Resistance Factor Design (LRFD) codes
- Includes realistic design examples covering large-scale, high-rise building structures
- Presents computational models that enable substantial cost savings in the design of structures
Fully automated structural design and cost optimization is where large-scale design technology is heading, thus Cost Optimization of Structures: Fuzzy Logic, Genetic Algorithms, and Parallel Computing will be of great interest to civil and structural engineers, mechanical engineers, structural design software developers, and architectural engineers involved in the design of structures and life-cycle cost optimisation. It is also a pioneering text for graduate students and researchers working in building design and structural optimization.
Kamal C. Sarma is a Senior Bridge Engineer at Barr & Prevost in Columbus, Ohio. He is a registered Professional Engineer in the state of Ohio. He has more than 25 years of work experience in Civil and Structural Engineering and has designed numerous multi-span highway bridges in the state of Ohio. He obtained his Bachelor of Engineering degree in 1976 from Jorhat Engineering College in India and obtained his Master of Structural Engineering degree from University of Roorkee, India in 1984. He received his PhD in Civil Engineering from The Ohio State University in 2001. He worked as a Lecturer and an Assistant Professor in Assam Engineering College for 12 years where he taught courses on design of reinforced concrete and steel structures. As an expert consultant, the Government of Assam selected him as a member of a three-member committee assigned to investigate the development of cracks in the foundation of a thermal power station in Chandrapur, Assam, India. In the United States he also worked as a Senior Software Development Engineer for Qwest Communications and a Field Engineer for K&S Engineers in Highland, Indiana. He performed construction inspection of several multi-storied structures in the Chicago area. He has also consulted in the areas of geotechnical and foundation engineering including slurry wall construction. He is the co-author of 10 research articles in the areas of structural optimization, genetic algorithms, fuzzy systems, and high-performance computing including parallel processing, published in several international research journals.
About the Authors.
1.1 The Case for Cost Optimization.
1.2 Cost Optimization of Concrete Structures.
1.3 Cost Optimization of Steel Structures.
2 Evolutionary Computing and Genetic Algorithm.
2.1 Overview and Basic Operations.
2.2 Coding and Decoding.
2.3 Basic Operations in Genetic Algorithm.
2.4 GA with Penalty Function Method.
2.5 Augmented LaGrange Method.
2.6 GA with Augmented Lagrangian Method.
3 Cost Optimization of Composite Floors.
3.2 Minimum Cost Design of Composite Beams.
3.3 Solution by Floating-Point Genetic Algorithm.
3.4 Solution by Neural Dynamics Method.
3.5 Counter Propagation Neural (CPN) Network.
For Function Approximation.
4 Fuzzy Genetic Algorithm for Optimization of Steel Structures.
4.2 Fuzzy Set Theory and Structural Optimization.
4.3 Minimum Weight Design of Axially Loaded Space Structures.
4.4 Fuzzy Membership Functions.
4.5 Fuzzy Augmented Lagrangian Genetic Algorithm.
4.6 Implementation and Examples.
5 Fuzzy Discrete Multi-criteria Cost Optimization of Steel Structures.
5.1 Cost of a Steel Structure.
5.2 Cost of a Steel Structure and the Primary Contributing Factors.
5.3 Fuzzy Discrete Multi-criteria Cost Optimization.
5.4 Membership Functions.
5.5 Fuzzy Membership Functions for Criteria with Unequal Importance.
5.6 Pareto Optimality.
5.7 Selection of Commercially Available Discrete Shapes.
5.8 Implementation and Parametric Study.
5.9 Application to High-rise Steel Structures.
5.10 Concluding Comments.
6 Parallel Computing.
6.1 Multiprocessor Computing Environment.
6.2 Parallel Processing Implementation Environment.
6.3 Performance Optimization of Parallel Programs.
7 Parallel Fuzzy Genetic Algorithm for Cost Optimization of Large Steel Structures.
7.1 Genetic Algorithm and Parallel Processing.
7.2 Cost Optimization of Moment-Resisting Steel Space Structures.
7.3 Data Parallel Fuzzy Genetic Algorithm for Optimization of Steel Structures Using OpenMP.
7.4 Distributed Parallel Fuzzy Genetic Algorithm for Optimization of Steel Structures Using MPI.
7.5 Bi-level Parallel Fuzzy GA for Optimization of Steel Structures Using OpenMP and MPI.
7.6 Application to High-rise Building Steel Structures.
7.7 Parallel Processing Performance Evaluation.
7.8 Concluding Comments.
8. Life Cycle Cost Optimization of Steel Structures.
8.2 Life Cycle Cost of a Steel Structure and the Primary Contributing Factors.
8.3 Formulation of Total Life Cycle Cost.
8.4 Fuzzy Discrete Multi-criteria Life Cycle Cost Optimization.
8.5 Application to a High-rise Building Steel Structure.
Cross-sectional areas, perimeter, and costs in US dollars for different W-shapes used for axially loaded members.
Cross-sectional areas, perimeter, and costs in US dollars for different W-shapes used for laterally loaded members.