Global Optimization in Engineering Design / Edition 1

by Ignacio E. Grossmann

Overview

Mathematical Programming has been of significant interest and relevance in engineering, an area that is very rich in challenging optimization problems. In particular, many design and operational problems give rise to nonlinear and mixed-integer nonlinear optimization problems whose modeling and solu­ tion is often nontrivial. Furthermore, with the increased computational power and development of advanced analysis (e. g. , process simulators, finite element packages) and modeling systems (e. g. , GAMS, AMPL, SPEEDUP, ASCEND, gPROMS), the size and complexity of engineering optimization models is rapidly increasing. While the application of efficient local solvers (nonlinear programming algorithms) has become widespread, a major limitation is that there is often no guarantee that the solutions that are generated correspond to global optima. In some cases finding a local solution might be adequate, but in others it might mean incurring a significant cost penalty, or even worse, getting an incorrect solution to a physical problem. Thus, the need for finding global optima in engineering is a very real one. It is the purpose of this monograph to present recent developments of techniques and applications of deterministic approaches to global optimization in engineering. The present monograph is heavily represented by chemical engineers; and to a large extent this is no accident. The reason is that mathematical programming is an active and vibrant area of research in chemical engineering. This trend has existed for about 15 years.

Product Details

ISBN-13:	9781441947543
Publisher:	Springer US
Publication date:	12/10/2010
Series:	Nonconvex Optimization and Its Applications , #9
Edition description:	Softcover reprint of the original 1st ed. 1996
Pages:	388
Product dimensions:	6.10(w) x 9.25(h) x 0.03(d)

Table of Contents

1. Branch and Bound for Global NLP: New Bounding LP.- 2. Branch and Bound for Global NLP: Iterative LP Algorithm & Results.- 3. New Formulations and Branching Strategies for the GOP Algorithm.- 4. Computational Results for an Efficient Implementation of the GOP Algorithm and Its Variants.- 5. Solving Nonconvex Process Optimisation Problems Using Interval Subdivision Algorithms.- 6. Global Optimization of Nonconvex MINLP’s by Interval Analysis.- 7. Planning of Chemical Process Networks via Global Concave Minimization.- 8. Global Optimization for Shastic Planning, Scheduling and Design Problems.- 9. Global Optimization of Heat Exchanger Networks with Fixed Configuration for Multiperiod Design.- 10. Alternative Bounding Approximations for the Global Optimization of Various Engineering Design Problems.- 11. A Pipe Reliability and Cost Model for an Integrated Approach Toward Designing Water Distribution Systems.- 12. Global Optimisation of General Process Models.

Editorial Reviews

Emphasizing chemical engineering, presents to engineers and researchers in optimization some of the recent developments in finding global optima, especially techniques and applications of deterministic approaches. Describes several algorithms including an LP-based branch and bound search, an enhanced GOP algorithm, and interval analysis methods. Also describes applications in planning process networks, stochastic scheduling, heat exchanger networks, layout design, truss design, multiproduct batch plants, and water distribution systems. No index. Annotation c. Book News, Inc., Portland, OR (booknews.com)

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