Constrained Optimization and Lagrange Multiplier Methods
The area of Lagrange multiplier methods for constrained minimization has undergone a radical transformation starting with the introduction of augmented Lagrangian functions and methods of multipliers in 1968 by Hestenes and Powell. The initial success of these methods in computational practice motivated further efforts aimed at understanding and improving their properties. At the same time their discovery provided impetus and a new perspective for reexaminations of Lagrange multiplier methods proposed and nearly abandoned several years earlier. These efforts, aided by fresh ideas based on exact penalty functions, have resulted in a variety of interesting methods utilizing Lagrange multiplier iterations and competing with each other for solution of different classes of problems.
This monograph is the outgrowth of the author's research involvement in the area of Lagrange multiplier methods over a nine-year period beginning in early 1972. It is aimed primarily toward researchers and practitioners of mathematical programming algorithms, with a solid background in introductory linear algebra and real analysis.
Considerable emphasis is placed on the method of multipliers which, together with its many variations, may be viewed as a primary subject of the monograph. Chapters 2, 3, and 5 are devoted to this method. A large portion of Chapter 1 is devoted to unconstrained minimization algorithms on which the method relies. The developments on methods of multipliers serve as a good introduction to other Lagrange multiplier methods examined in Chapter 4.
Several results and algorithms were developed as the monograph was being written and have not as yet been published in journals. These include the algorithm for minimization subject to simple constraints (Section 1.5), the improved convergence and rate-of-convergence results of Chapter 2, the first stepsize rule of Section 2.3.1, the unification of the exact penalty methods of DiPillo and Grippo, and Fletcher, and their relationship with Newton's method (Section 4.3), the globally convergent Newton and quasi-Newton methods based on differentiable exact penalty functions (Section 4.5.2) , and the methodology for solving large-scale separable integer programming problems of Section 5.6.
The line of development of the monograph is based on the author's conviction that solving practical nonlinear optimization problems efficiently (or at all) is typically a challenging undertaking and can be accomplished only through a thorough understanding of the underlying theory. This is true even if a polished packaged optimization program is used, but more so when the problem is large enough or important enough to warrant the development of a specialized algorithm. Furthermore, it is quite common in practice that methods are modified, combined, and extended in order to construct an algorithm that matches best the features of the particular problem at hand, and such modifications require a full understanding of the theoretical foundations of the method utilized. For these reasons, we place primary emphasis on the principles of underlying various methods and the analysis of their convergence and rate-of-converge properties. We also provide extensive guidance on the merits of various types of methods but, with a few exceptions, do not provide any algorithms that are specified to the last level of detail.
The monograph is based on the collective works of many researchers as well as my own. Of those people whose work had a substantial influence on my thinking and contributed in an important way to the monograph I would like to mention J.\ D. Buys, G. DiPillo, L. Dixon, R. Fletcher, T. Glad, L. Grippo, M. Hestenes, D. Luenberger, O. Mangasarian, D. Q. Mayne, E. Polak, B. T. Poljak, M. J. D. Powell, B. Pschenichny, R. T. Rockafellar, and R. Tapia. My research on methods of multipliers began at Stanford University. My interaction there with Daniel Gabay, Barry Kort, and David Luenberger had a lasting influence on my subsequent work on the subject. The material of Chapter 5 in particular is largely based on the results of my direct collaboration with Barry Kort. The material of Section 5.6 is based on work on electric power system scheduling at Alphatech, Inc. where I collaborated with Greg Lauer, Tom Posbergh, and Nils R. Sandell, Jr.
Finally, I wish to acknowledge gratefully the research support of the National Science Foundation, and the expert typing of Margaret Flaherty, Leni Gross, and Rosalie J. Bialy.
Dimitri P. Bertsekas