Global Optimization in Engineering Design

1. Front Matter

   Pages i-ix

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2. Branch and Bound for Global NLP: New Bounding LP

   • Thomas G. W. Epperly, Ross E. Swaney

   Pages 1-35

3. Branch and Bound for Global NLP: Iterative LP Algorithm & Results

   • Thomas G. W. Epperly, Ross E. Swaney

   Pages 37-73

4. New Formulations and Branching Strategies for the GOP Algorithm

   • V. Visweswaran, C. A. Floudas

   Pages 75-109

5. Computational Results for an Efficient Implementation of the GOP Algorithm and Its Variants

   • V. Visweswaran, C. A. Floudas

   Pages 111-153

6. Solving Nonconvex Process Optimisation Problems Using Interval Subdivision Algorithms

   • R. P. Byrne, I. D. L. Bogle

   Pages 155-174

7. Global Optimization of Nonconvex MINLP’s by Interval Analysis

   • Ragavan Vaidyanathan, Mahmoud El-Halwagi

   Pages 175-193

8. Planning of Chemical Process Networks via Global Concave Minimization

   • Ming-Long Liu, Nikolaos V. Sahinidis, J. Parker Shectman

   Pages 195-230

9. Global Optimization for Stochastic Planning, Scheduling and Design Problems

   • M. G. Ierapetritou, E. N. Pistikopoulos

   Pages 231-287

10. Global Optimization of Heat Exchanger Networks with Fixed Configuration for Multiperiod Design

    • Ramaswamy R. Iyer, Ignacio E. Grossmann

    Pages 289-308

11. Alternative Bounding Approximations for the Global Optimization of Various Engineering Design Problems

    • I. Quesada, I. E. Grossmann

    Pages 309-331

12. A Pipe Reliability and Cost Model for an Integrated Approach Toward Designing Water Distribution Systems

    • Hanif D. Sherali, Ernest P. Smith, Seong-in Kim

    Pages 333-354

13. Global Optimisation of General Process Models

    • Edward M. B. Smith, Constantinos C. Pantelides

    Pages 355-386

14. Back Matter

    Pages 387-387

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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 program­ ming 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 tech­ niques and applications of deterministic approaches to global optimization in engineering. The present monograph is heavily represented by chemical engi­ neers; 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.

• RSI
• algorithms
• calculus
• engineering design
• linear optimization
• modeling
• nonlinear optimization
• optimization

• Carnegie Mellon University, USA

  Ignacio E. Grossmann

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