This volume contains the papers selected for presentation at IPCO VII, the Seventh Conference on Integer Programming and Combinatorial Optimization, Graz, Austria, June9{11,1999.Thismeetingisaforumforresearchersandpr- titioners working on various aspects of integer programming and combinatorial optimization. The aim is to present recent developments in theory, compu- tion, and applications of integer programming and combinatorial optimization. Topics include, but are not limited to: approximation algorithms, branch and bound algorithms, computational biology, computational complexity, compu- tional geometry, cutting plane algorithms, diophantine equations, geometry of numbers, graph and network algorithms, integer programming, matroids and submodular functions, on-line algorithms, polyhedral combinatorics, scheduling theory and algorithms, and semide nite programs. IPCO was established in 1988 when the rst IPCO program committee was formed. IPCO I took place in Waterloo (Canada) in 1990, IPCO II was held in Pittsburgh (USA) in 1992, IPCO III in Erice (Italy) 1993, IPCO IV in Cop- hagen (Denmark) 1995, IPCO V in Vancouver (Canada) 1996, and IPCO VI in Houston (USA) 1998. IPCO is held every year in which no MPS (Mathematical Programming Society) International Symposium takes place: 1990, 1992, 1993, 1995,1996,1998,1999,2001,2002,2004,2005,2007,2008: ::::: Since the MPS meeting is triennial, IPCO conferences are held twice in everythree-year period. As a rule, in even years IPCO is held somewhere in Northern America, and in odd years it is held somewhere in Europe. In response to the call for papers for IPCO 99, the program committee - ceived99submissions, indicatingastrongandgrowinginterestintheconfere

Optimization methods play a central role in financial modeling. This textbook is devoted to explaining how state-of-the-art optimization theory, algorithms, and software can be used to efficiently solve problems in computational finance. It discusses some classical mean-variance portfolio optimization models as well as more modern developments such as models for optimal trade execution and dynamic portfolio allocation with transaction costs and taxes. Chapters discussing the theory and efficient solution methods for the main classes of optimization problems alternate with chapters discussing their use in the modeling and solution of central problems in mathematical finance. This book will be interesting and useful for students, academics, and practitioners with a background in mathematics, operations research, or financial engineering. The second edition includes new examples and exercises as well as a more detailed discussion of mean-variance optimization, multi-period models, and additional material to highlight the relevance to finance.

Optimization models play an increasingly important role in financial decisions. This is the first textbook devoted to explaining how recent advances in optimization models, methods and software can be applied to solve problems in computational finance more efficiently and accurately. Chapters discussing the theory and efficient solution methods for all major classes of optimization problems alternate with chapters illustrating their use in modeling problems of mathematical finance. The reader is guided through topics such as volatility estimation, portfolio optimization problems and constructing an index fund, using techniques such as nonlinear optimization models, quadratic programming formulations and integer programming models respectively. The book is based on Master's courses in financial engineering and comes with worked examples, exercises and case studies. It will be welcomed by applied mathematicians, operational researchers and others who work in mathematical and computational finance and who are seeking a text for self-learning or for use with courses.

This book is an elegant and rigorous presentation of integer programming, exposing the subject's mathematical depth and broad applicability. Special attention is given to the theory behind the algorithms used in state-of-the-art solvers. An abundance of concrete examples and exercises of both theoretical and real-world interest explore the wide range of applications and ramifications of the theory. Each chapter is accompanied by an expertly informed guide to the literature and special topics, rounding out the reader's understanding and serving as a gateway to deeper study. Key topics include: formulations polyhedral theory cutting planes decomposition enumeration semidefinite relaxations Written by renowned experts in integer programming and combinatorial optimization, Integer Programming is destined to become an essential text in the field.

This monograph presents new and elegant proofs of classical results and makes difficult results accessible. The integer programming models known as set packing and set covering have a wide range of applications. Sometimes, owing to the special structure of the constraint matrix, the natural linear programming relaxation yields an optimal solution that is integral, thus solving the problem. Sometimes, both the linear programming relaxation and its dual have integral optimal solutions. Under which conditions do such integrality conditions hold? This question is of both theoretical and practical interest. Min-max theorems, polyhedral combinatorics, and graph theory all come together in this rich area of discrete mathematics. This monograph presents several of these beautiful results as it introduces mathematicians to this active area of research. To encourage research on the many intriguing open problems that remain, Dr. Cornuejols is offering a $5000 prize to the first paper solving or refuting each of the 18 conjectures described in the book. To claim one of the prizes mentioned in the preface, papers must be accepted by a quality refereed journal (such as Journal of Combinatorial Theory B, Combinatorica, SIAM Journal on Discrete Mathematics, or others to be determined by Dr. Cornuejols) before 2020. Claims must be sent to Dr. Cornuejols at Carnegie Mellon University during his lifetime.