STATE OF NONLINEAR OPTIMIZATION CODES AND EMPIRICAL TESTS *Leon Lasdon (University of Texas at Austin) and *Ken Ragsdell (Purdue University) E. D. Eason (Failure Analysis Associates) "Evidence of Fundamental Difficulties in Nonlinear ...

Lootsma, F.A., Performance Evaluation of Nonlinear Optimization Methods via Multi-Criteria Decision Analysis and via Linear Model Analysis. In M. J.D. Powell (ed.), Nonlinear Optimization 1981. Academic Press, London, 419–453, 1982.

Author: Klaus Schittkowski

Publisher: Springer Science & Business Media

ISBN: 9783642824500

Category: Mathematics

Page: 451

View: 206

This book contains the written versions of main lectures presented at the Advanced Study Institute (ASI) on Computational Mathematical Programming, which was held in Bad Windsheim, Germany F. R., from July 23 to August 2, 1984, under the sponsorship of NATO. The ASI was organized by the Committee on Algorithms (COAL) of the Mathematical Programming Society. Co-directors were Karla Hoffmann (National Bureau of Standards, Washington, U.S.A.) and Jan Teigen (Rabobank Nederland, Zeist, The Netherlands). Ninety participants coming from about 20 different countries attended the ASI and contributed their efforts to achieve a highly interesting and stimulating meeting. Since 1947 when the first linear programming technique was developed, the importance of optimization models and their mathematical solution methods has steadily increased, and now plays a leading role in applied research areas. The basic idea of optimization theory is to minimize (or maximize) a function of several variables subject to certain restrictions. This general mathematical concept covers a broad class of possible practical applications arising in mechanical, electrical, or chemical engineering, physics, economics, medicine, biology, etc. There are both industrial applications (e.g. design of mechanical structures, production plans) and applications in the natural, engineering, and social sciences (e.g. chemical equilibrium problems, christollography problems).

CHAPTER 17 MATHEMATICAL PROGRAMMING METHODS FOR THE EVALUATION OF DYNAMIC PLASTIC DEFORMATIONS G. Borino , S. Caddemi and C. Polizzotto University of Palermo , Palermo , Italy ABSTRACT Dynamic plastic deformation can be evaluated with ...

Author: D. Lloyd Smith

Publisher: Springer Science & Business Media

ISBN: 3211821910

Category: Language Arts & Disciplines

Page: 435

View: 501

Civil engineering structures tend to be fabricated from materials that respond elastically at normal levels of loading. Most such materials, however, would exhibit a marked and ductile inelasticity if the structure were overloaded by accident or by some improbable but naturally occuring phenomeon. Indeed, the very presence of such ductility constitutes an important safety provision for large-scale constructions where human life is at risk. In the comprehensive evaluation of safety in structural design, it is therefore unrealistic not to consider the effects of ductility. This book sets out to show that the bringing together of the theory and methods of mathematical programming with the mathematical theory of plasticity furnishes a model which has a unifying theoretical nature and is entirely representative of observed structural behaviour. The contents of the book provide a review of the relevant aspects of mathematical programming and plasticity theory, together with a detailed presentation of the most interesting and potentially useful applications in both framed and continuum structures: ultimate strength and elastoplastic deformability; shakedown and practical upper bounds on deformation measures; evolutive dynamic response; large displacements and instability; stochastic and fuzzy programming for representing uncertainty in ultimate strength calculations. Besides providing a ready fund of computational algorithms, mathematical programming invests applications in mechanics with a refined mathematical formalism, rich in fundamental theorems, which often gives addi- tional insight into known results and occasionally lead to new ones. In addition to its obvious practical utility, the educational value of the material thoroughly befits a university discipline.

160: Integer Programming and Related Areas. A Classified Bibliography. ... 164: C. L. Hwang and A. S. M. Masud, Multiple Objective Decision Making – Methods and Applications. ... 199: Evaluating Mathematical Programming Techniques.

Author: M.H. Karwan

Publisher: Springer Science & Business Media

ISBN: 9783642455353

Category: Business & Economics

Page: 290

View: 648

During the Spring of 1979 one of us (Zionts) was invited to visit Erasmus University in Rotterdam, The Netherlands. It was there that Zionts met another of us (Telgen) who was then in the process of completing a dissertation on redundancy in linear programming. At that time, Telgen proposed an extended visit to Buffalo, during which time he and Zionts would do an extensive study on redundancy. Redundancy, hardly an exciting or new topic, does have numerous applications. Telgen and Zionts planned the project for the Summer of 1980, and enlisted the support of all the contributors as well as the other two members of our team (Karwan and Lotfi). Lotfi was then a Ph. D. student in Industrial Engineering searching for a thesis topic. Redundancy became his topic. Karwan and Zionts served as his thesis co-chairmen, with Telgen serving as an outside reader of the thesis. We initially had hoped to complete the study during Telgen's stay in Buffalo, but that was far too optimistic. Lotfi completed his dissertation during the late Spring-early Summer of 1981. As the project took shape, we decided that we had more than enough for an article, or even several articles. Accordingly, not wanting to produce redundant papers, we decided to produce this volume --- a state-of-the-art review of methods for handling redundancy and comprehensive tests of the various methods, together with extensions and further developments of the most promising methods.

Crowder H. ( 1982 ) Mathematical programming algorithms in APL . In Evaluating Mathematical Programming Techniques , Edited by J.M. Mulvey , pp.290-304 . New York : Springer - Verlag . 4 . Sniedovich M. ( 1989 ) The APL phenomenon : an ...

Author: Santosh Kumar

Publisher: CRC Press

ISBN: 2881248209

Category: Mathematics

Page: 457

View: 552

This book is concerned with theoretical developments in the area of mathematical programming including new algorithms (analytic and heuristic) and their applications in science and industry. It exposes recent mathematical developments to a larger audience in science and industry who may not be equipped with the necessary research background and provides good references in many branches of mathematical programming. The text includes research and tutorial papers giving details of use of recent developments in applied areas, as well as review and state-of-the-art papers providing a soruce of references to researchers in this field.

184: R. E. Burkard and U. Derigs, Assignment and Matching Problems: Solution Methods with FORTRAN-Programs. VIII, 148 pages. 1980. Vol.185. ... 199: Evaluating Mathematical Programming Techniques. Proceedings, 1981.

Author: Volker Firchau

Publisher: Springer Science & Business Media

ISBN: 9783642492723

Category: Business & Economics

Page: 108

View: 944

An investor who wants to invest a certain amount and to whom a lot of more or less risky alternatives arise would divide this amount among several securities. He makes this portfolio decision because of his expectations with regard to these assets which result from the information available to him. If the investor obtains additional information, then his knowledge would improve and, therefore, the portfolio decision made by him. Accordingly, he will be ready to accept certain costs related to the information procurement. The value of information indicates the maximum tolerable information costs, and its knowledge, therefore, enables - by comparing with the actual information costs - to evaluate the profitability of an information procurement. In this book, the value of information for the problem of portfolio planning is explicitly determined, namely as well for the case of fixed prices not influenced by the information activity as within the scope of a market model. These explicit results allow several conclusions, in particular about the influence of preknowledge, risk aversion, information precision and information dissemination on their value. The Bayesian decision theory is the basis for this paper. Corres pondingly, a subjective concept of probability is underlying, and the information processing and evaluation is understood in a sta tistical sense. As one might expect, the question about the correct ness of an information is not treated, although manipulating the asset prices by deliberate dis information can be observed in prac tice and is, certainly, an interesting problem.

Author: United States. National Bureau of StandardsPublish On: 1977

Keywords : Code comparison ; comparison of mathematical programming software ; evaluation ; testing . 1. Introduction Computational experiments with mathematical programming techniques have taken place throughout the past twenty - five ...

Author: United States. National Bureau of Standards

Evaluating mathematical programming techniques . Springer Verlag , 1982 . ( 116 ) B. A. Murtagh . Advanced linear programming : Computation and practice . McGrawHill , 1981 . ( 117 ) B. A. Murtagh and M. A. Saunders .

Author: Janos Mayer

Publisher: CRC Press

ISBN: 9056991442

Category: Computers

Page: 163

View: 797

A computationally oriented comparison of solution algorithms for two stage and jointly chance constrained stochastic linear programming problems, this is the first book to present comparative computational results with several major stochastic programming solution approaches. The following methods are considered: regularized decomposition, stochastic decomposition and successive discrete approximation methods for two stage problems; cutting plane methods, and a reduced gradient method for jointly chance constrained problems. The first part of the book introduces the algorithms, including a unified approach to decomposition methods and their regularized counterparts. The second part addresses computer implementation of the methods, describes a testing environment based on a model management system, and presents comparative computational results with the various algorithms. Emphasis is on the computational behavior of the algorithms.