How we did it:
For any feedback, any questions, any notes or just for chat - feel free to follow us on social networks
This book emphasizes the creative aspects of algorithm design by examining steps used in the process of algorithm development. The heart of the creative process lies in an analogy between proving mathematical theorems by induction and designing combinatorial algorithms. The book contains hundreds of problems and examples. It is designed to enhance the reader's problem-solving abilities and understanding of the principles behind algorithm design. 0201120372B04062001
Vijay V. Vazirani
Covering the basic techniques used in the latest research work, the author consolidates progress made so far, including some very recent and promising results, and conveys the beauty and excitement of work in the field. He gives clear, lucid explanations of key results and ideas, with intuitive proofs, and provides critical examples and numerous illustrations to help elucidate the algorithms. Many of the results presented have been simplified and new insights provided. Of interest to theoretical computer scientists, operations researchers, and discrete mathematicians.
Laurence A. Wolsey
A practical, accessible guide to optimization problems with discrete or integer variables Integer Programming stands out from other textbooks by explaining in clear and simple terms how to construct custom-made algorithms or use existing commercial software to obtain optimal or near-optimal solutions for a variety of real-world problems, such as airline timetables, production line schedules, or electricity production on a regional or national scale. Incorporating recent developments that have made it possible to solve difficult optimization problems with greater accuracy, author Laurence A. Wolsey presents a number of state-of-the-art topics not covered in any other textbook. These include improved modeling, cutting plane theory and algorithms, heuristic methods, and branch-and-cut and integer programming decomposition algorithms. This self-contained text: * Distinguishes between good and bad formulations in integer programming problems * Applies lessons learned from easy integer programs to more difficult problems * Demonstrates with applications theoretical and practical aspects of problem solving * Includes useful notes and end-of-chapter exercises * Offers tremendous flexibility for tailoring material to different needs Integer Programming is an ideal text for courses in integer/mathematical programming-whether in operations research, mathematics, engineering, or computer science departments. It is also a valuable reference for industrial users of integer programming and researchers who would like to keep up with advances in the field.
Wayne L. Winston, Jeffrey B. Goldberg
An introduction to model building; Basic linear algebra; Introduction to linear programming; The simplex algorithm and goal programming; Sensititivity analysis: an applied approach; Sensitivity analysis and duality; Transportation, assignment, and transshipment problems; Network models; Integer programming; Advanced topics in linear programming; Nonlinear programming; Review of calculus and probality; Decision making under uncertainty; Game theory; Deterministic EOQ inventory models; Probabilistic EOQ inventory models; Makov Chains; Deterministic dynamic programming; Probabilistic dynamic programming; Queuing theory; Simulation; Simulation with process model; Spreadheet simulation with the excel add-in@risk; Forecasting models.
Hans Kellerer, Ulrich Pferschy, David Pisinger
Thirteen years have passed since the seminal book on knapsack problems by Martello and Toth appeared. On this occasion a former colleague exclaimed back in 1990: "How can you write 250 pages on the knapsack problem?" Indeed, the definition of the knapsack problem is easily understood even by a non-expert who will not suspect the presence of challenging research topics in this area at the first glance. However, in the last decade a large number of research publications contributed new results for the knapsack problem in all areas of interest such as exact algorithms, heuristics and approximation schemes. Moreover, the extension of the knapsack problem to higher dimensions both in the number of constraints and in the num ber of knapsacks, as well as the modification of the problem structure concerning the available item set and the objective function, leads to a number of interesting variations of practical relevance which were the subject of intensive research during the last few years. Hence, two years ago the idea arose to produce a new monograph covering not only the most recent developments of the standard knapsack problem, but also giving a comprehensive treatment of the whole knapsack family including the siblings such as the subset sum problem and the bounded and unbounded knapsack problem, and also more distant relatives such as multidimensional, multiple, multiple-choice and quadratic knapsack problems in dedicated chapters.