Mode of access: World Wide Web.

System requirements: Adobe Acrobat Reader.

Part of: Synthesis digital library of engineering and computer science.

Includes bibliographical references and index.

Part I. Introduction, history, and theoretical fundamentals of geometric programming -- 1. Introduction -- 1.1 Optimization and geometric programming -- 1.1.1 Optimization -- 1.1.2 Geometric programming -- 1.2 Evaluative questions -- 1.3 References -- 2.Brief history of geometric programming -- 2.1 Pioneers of geometric programming -- 2.2 Evaluative questions -- 2.3 References -- 3. Theoretical fundamentals -- 3.1 Primal and dual formulations -- 3.2 Evaluative questions -- 3.3 References --

Part II. Geometric programming cost minimization applications with zero degrees of difficulty -- 4. The optimal box design case study -- 4.1 Introduction -- 4.2 The optimal box design problem -- 4.3 Evaluative questions -- 5. Trash can case study -- 5.1 Introduction -- 5.2 The optimal trash can design problem -- 5.3 Evaluative questions -- 5.4 References -- 6. The building area design case study -- 6.1 Introduction -- 6.2 The building area design problem -- 6.3 Problem solution -- 6.4 Modified building area design problem -- 6.5 Fixed room height area design problem -- 6.6 Evaluative questions -- 6.7 References -- 7. The open cargo shipping box case study -- 7.1 Problem statement and general solution -- 7.2 Evaluative questions -- 7.3 References -- 8. Metal casting cylindrical side riser case study -- 8.1 Introduction -- 8.2 Problem formulation and general solution -- 8.3 Cylindrical side riser example -- 8.4 Evaluative questions -- 8.5 References -- 9. Inventory model case study -- 9.1 Problem statement and general solution -- 9.2 Inventory example problem -- 9.3 Evaluative questions -- 9.4 References -- 10. Process furnace design case study -- 10.1 Problem statement and solution -- 10.2 Conclusions -- 10.3 Evaluative questions -- 10.4 References -- 11. The gas transmission pipeline case study -- 11.1 Problem statement and solution -- 11.2 Evaluative questions -- 11.3 References -- 12. Material removal/metal cutting economics case study -- 12.1 Introduction -- 12.2 Problem formulation -- 12.3 Evaluative questions -- 12.4 References -- 13. Construction building sector cost minimization case study -- 13.1 Introduction -- 13.2 Model development -- 13.3 Model results and validation -- 13.4 Conclusions -- 13.5 Evaluative questions -- 13.6 References --

Part III. Geometric programming profit maximization applications with zero degrees of difficulty -- 14. Production function profit maximization case study -- 14.1 Profit maximization with geometric programming -- 14.2 Profit maximization of the production function case study -- 14.3 Evaluative questions -- 14.4 References -- 15. Product mix profit maximization case study -- 15.1 Profit maximization using the Cobb-Douglas production function -- 15.2 Evaluative questions -- 15.3 References -- 16. Chemical plant product profitability case study -- 16.1 Model formulation -- 16.2 Primal and dual solutions -- 16.3 Evaluative questions -- 16.4 References --

Part IV. Geometric programming applications with positive degrees of difficulty -- 17. Journal bearing design case study -- 17.1 Issues with positive degrees of difficulty problems -- 17.2 Journal bearing case study -- 17.3 Primal and dual formulation of journal bearing design -- 17.4 Dimensional analysis technique for additional equation -- 17.5 Evaluative questions -- 17.6 References -- 18. Multistory building design with a variable number of floors case study -- 18.1 Introduction -- 18.2 Problem formulation -- 18.3 Evaluative questions -- 18.4 References -- 19. Metal casting cylindrical side riser with hemispherical top design case study -- 19.1 Introduction -- 19.2 Problem formulation -- 19.3 Dimensional analysis technique for additional two equations -- 19.4 Evaluative questions -- 19.5 References -- 20. Liquefied petroleum gas (LPG) cylinders case study -- 20.1 Introduction -- 20.2 Problem formulation -- 20.3 Dimensional analysis technique for additional equation -- 20.4 Evaluative questions -- 20.5 References -- 21. Material removal/metal cutting economics with two constraints case study -- 21.1 Introduction -- 21.2 Problem formulation -- 21.3 Problem solution -- 21.4 Example problem -- 21.5 Evaluative questions -- 21.6 References -- 22. The open cargo shipping box with skids case study -- 22.1 Introduction -- 22.2 Primal and dual problem formulation -- 22.3 Constrained derivative approach -- 22.4 Dimensional analysis approach for additional equation -- 22.5 Condensation of terms approach -- 22.6 Evaluative questions -- 22.7 References -- 23. Profit maximization considering decreasing cost functions of inventory policy case study -- 23.1 Introduction -- 23.2 Model formulation -- 23.3 Inventory example problem with scaling constants for price and cost -- 23.4 Transformed dual approach -- 23.5 Evaluative questions -- 23.6 References --

Part V. Summary, future directions, theses and dissertations on geometric programming -- 24. Summary and future directions -- 24.1 Summary -- 24.2 Future directions -- 24.3 Development of new design relationships -- 25. Theses and dissertations on geometric programming -- 25.1 Introduction -- 25.2 Lists of M.S. theses and Ph.D. dissertations -- Author's biography -- Index.

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Geometric Programming is used for cost minimization, profit maximization, obtaining cost ratios, and the development of generalized design equations for the primal variables. The early pioneers of geometric programming--Zener, Duffin, Peterson, Beightler, Wilde, and Phillips-- played important roles in its development. Five new case studies have been added to the third edition. There are five major sections: (1) Introduction, History and Theoretical Fundamentals; (2) Cost Minimization Applications with Zero Degrees of Difficulty; (3) Profit Maximization Applications with Zero Degrees of Difficulty; (4) Applications with Positive Degrees of Difficulty; and (5) Summary, Future Directions, and Geometric Programming Theses & Dissertations Titles. The various solution techniques presented are the constrained derivative approach, condensation of terms approach, dimensional analysis approach, and transformed dual approach. A primary goal of this work is to have readers develop more case studies and new solution techniques to further the application of geometric programming.

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Title from PDF title page (viewed on January 24, 2017).