This volume contains the Proceedings of the Sixth French-German Conference on Optimization, which took place in June 1991 at Lambrecht (PfaIz). About one hundred scientists, mainly from France and Germany, but also from other european countries, met at the Palatinate Conference Center in the heart of the beautiful palatinate national park to review and discuss recent developments in the field of optimization. More than sixty lectures were delivered, covering a large part of the theoretical and practical aspects of optimization. They all contributed to a stimulating scientific exchange during the meeting. This conference was the sixth in a series which started in 1980. Proceedings of the previous French-German Conferences on Optimization have been published as follows: First Conference (Oberwolfach 1980): Optimization and Optimal Control, edited by A. Auslender, W. Oettli and J. Stoer (Lecture Notes in Control and Information Sciences, 30). Springer Verlag, Berlin and Heidelber. e;, 1981 Second Conference (Confolant, 1981): Optimization, edited by J. -B. Hiriart-Urruty, W. Oettli, J. Stoer (Lecture Notes in Pure and Applied Mathematics, 86). Marcel Dekker, New York and Basel1983 Third Conference (Lnminy, 1984): Third Franco-German Conference in Optimization, edited by C. Lemarechal. Institut National de Recherche en Informatique et en Automatique, Rocquencourt, 1984 (ISBN 2-7261-0402-9) Fourth Conference (Irsee, 1986): Trends in Mathematical Optimization, edited by K. Hoffmann, J. -B. Hiriart-Urruty, C. Lemarechal, J. Zowe (International Series of Numerical Mathematics, 84). Birkhauser Verlag, Basel and Boston 1988 Fifth Conference (Varetz, 1988): Optimization, edited by S.

It is already a tradition that conferences on operations research are organized by the Mathematisches Forschungsinstitut in Oberwolfach/Germany. The mean point of the 1987 conference was to discuss recentl.v developed methods in optimization theory derived from various fields of mathematics. On the other hand, the practical use of results in operations research is very important. In the last few years* essenti.al progress in this direction was made at the International Insti- tute for Applied Systems Analysis (IIASA) at Laxenburg/Austria. Therefore a three days workshop on Advanced Computation Techniques, Parallel Processing and Optimi- zation organized by IIASA and the University of Karlsruhe immediately followed the Oberwolfach Conference. This volume contains selected pape~s which have been presented at one of these conferences. It:is divided into five sections based on the above topics: I. Algorithms and Optimization Methods II. Optimization and Parallel Processing III. Graph Theory and Scheduling IV. Differential Equations and Operator Theory V. Applications. We would like to thank the director of the Mathematisches Forschungsinstitut Oberwolfach Prof. Dr. M. Barner and the International Institute for Applied Systems Analysis, particularly Prof. Dr. V. Kaftanov, and also to the director of the Computer Center of the University of Karlsruhe Prof. Dr. A. Schreiner for their support in organizing these conferences. We also appreciate the excellent coopera- tion of Springer Verlag. We also thank Dr. P. Recht, Dr. D. Solte and Dr. K. Wieder as well as*Mrs.

The International Institute for Applied Systems Analysis (IIASA) in Laxenburg, Austria, has been involved in research on nondifferentiable optimization since 1976. IIASA-based East-West cooperation in this field has been very productive, leading to many important theoretical, algorithmic and applied results. Nondifferentiable optimi zation has now become a recognized and rapidly developing branch of mathematical programming. To continue this tradition, and to review recent developments in this field, IIASA held a Workshop on Nondifferentiable Optimization in Sopron (Hungary) in September 1964. The aims of the Workshop were: 1. To discuss the state-of-the-art of nondifferentiable optimization (NDO), its origins and motivation; 2. To compare-various algorithms; 3. To evaluate existing mathematical approaches, their applications and potential; 4. To extend and deepen industrial and other applications of NDO. The following topics were considered in separate sessions: General motivation for research in NDO: nondifferentiability in applied problems, nondifferentiable mathematical models. Numerical methods for solving nondifferentiable optimization problems, numerical experiments, comparisons and software. Nondifferentiable analysis: various generalizations of the concept of subdifferen tials. Industrial and other applications. This volume contains selected papers presented at the Workshop. It is divided into four sections, based on the above topics: I. Concepts in Nonsmooth Analysis II. Multicriteria Optimization and Control Theory III. Algorithms and Optimization Methods IV. Stochastic Programming and Applications We would like to thank the International Institute for Applied Systems Analysis, particularly Prof. V. Kaftanov and Prof. A.B. Kurzhanski, for their support in organiz ing this meeting."

Let eRN be the usual vector-space of real N-uples with the usual inner product denoted by (. ,. ). In this paper P is a nonempty compact polyhedral set of mN, f is a real-valued function defined on (RN continuously differentiable and fP is the line- ly constrained minimization problem stated as : min (f(x) I x EURO P) * For computing stationary points of problemtj) we propose a method which attempts to operate within the linear-simplex method structure. This method then appears as a same type of method as the convex-simplex method of Zangwill [6]. It is however, different and has the advantage of being less technical with regards to the Zangwill method. It has also a simple geometrical interpretation which makes it more under standable and more open to other improvements. Also in the case where f is convex an implementable line-search is proposed which is not the case in the Zangwill method. Moreover, if f(x) = (c,x) this method will coincide with the simplex method (this is also true in the case of the convex simplex method) i if f(x) = I Ixl 12 it will be almost the same as the algorithm given by Bazaraa, Goode, Rardin [2].

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