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Author: Dimitri P. Bertsekas
Publisher: MIT Press
Published: 1991
Total Pages: 384
ISBN-13: 9780262023344
DOWNLOAD EBOOKLinear Network Optimization presents a thorough treatment of classical approaches to network problems such as shortest path, max-flow, assignment, transportation, and minimum cost flow problems.
Author: Srinivas Shakkottai
Publisher: Now Publishers Inc
Published: 2008
Total Pages: 123
ISBN-13: 1601981023
DOWNLOAD EBOOKNetwork Optimization and Control is the ideal starting point for a mature reader with little background on the subject of congestion control to understand the basic concepts underlying network resource allocation.
Author: Mitsuo Gen
Publisher: Springer Science & Business Media
Published: 2008-07-10
Total Pages: 692
ISBN-13: 1848001819
DOWNLOAD EBOOKNetwork models are critical tools in business, management, science and industry. “Network Models and Optimization” presents an insightful, comprehensive, and up-to-date treatment of multiple objective genetic algorithms to network optimization problems in many disciplines, such as engineering, computer science, operations research, transportation, telecommunication, and manufacturing. The book extensively covers algorithms and applications, including shortest path problems, minimum cost flow problems, maximum flow problems, minimum spanning tree problems, traveling salesman and postman problems, location-allocation problems, project scheduling problems, multistage-based scheduling problems, logistics network problems, communication network problem, and network models in assembly line balancing problems, and airline fleet assignment problems. The book can be used both as a student textbook and as a professional reference for practitioners who use network optimization methods to model and solve problems.
Author: Fred Glover
Publisher: John Wiley & Sons
Published: 2011-10-14
Total Pages: 306
ISBN-13: 1118031423
DOWNLOAD EBOOKUnique in that it focuses on formulation and case studies ratherthan solutions procedures covering applications for pure,generalized and integer networks, equivalent formulations plussuccessful techniques of network models. Every chapter contains asimple model which is expanded to handle more complicateddevelopments, a synopsis of existing applications, one or more casestudies, at least 20 exercises and invaluable references. An Instructor's Manual presenting detailed solutions to all theproblems in the book is available upon request from the Wileyeditorial department.
Author: Ding-zhu Du
Publisher: World Scientific
Published: 1993-04-27
Total Pages: 417
ISBN-13: 9814504580
DOWNLOAD EBOOKIn the past few decades, there has been a large amount of work on algorithms for linear network flow problems, special classes of network problems such as assignment problems (linear and quadratic), Steiner tree problem, topology network design and nonconvex cost network flow problems.Network optimization problems find numerous applications in transportation, in communication network design, in production and inventory planning, in facilities location and allocation, and in VLSI design.The purpose of this book is to cover a spectrum of recent developments in network optimization problems, from linear networks to general nonconvex network flow problems./a
Author: Michael Watson
Publisher: Pearson Education
Published: 2013
Total Pages: 320
ISBN-13: 0133017370
DOWNLOAD EBOOKIntroduction and basic building blocks. Adding costs to two echelon supply chains. Advanced modeling and expanding to multiple echelons. How to get industrial streng results. Case study wrap up.
Author: Panos M. Pardalos
Publisher: Springer Science & Business Media
Published: 2012-12-06
Total Pages: 495
ISBN-13: 3642591795
DOWNLOAD EBOOKNetwork optimization is important in the modeling of problems and processes from such fields as engineering, computer science, operations research, transportation, telecommunication, decision support systems, manufacturing, and airline scheduling. Recent advances in data structures, computer technology, and algorithm development have made it possible to solve classes of network optimization problems that until recently were intractable. The refereed papers in this volume reflect the interdisciplinary efforts of a large group of scientists from academia and industry to model and solve complicated large-scale network optimization problems.
Author: V. Balakrishnan
Publisher: CRC Press
Published: 2019-08-16
Total Pages: 260
ISBN-13: 1000723089
DOWNLOAD EBOOKProblems in network optimization arise in all areas of technology and industrial management. The topic of network flows has applications in diverse fields such as chemistry, engineering, management science, scheduling and transportation, to name a few. Network Optimization introduces the subject to undergraduate and graduate students in computer science, mathematics and operations research. The focus is mainly on developing the mathematical underpinnings of the techniques that make it possible to solve the several optimization problems covered in the text. The text discusses such topics as optimal branching problems, transshipment problems, shortest path problems, minimum cost flow problems, maximum flow problems, matching in bipartite and nonbipartite graphs and many applications to combinatorics. Also included is a large number of exercises.
Author: Michael Neely
Publisher: Springer Nature
Published: 2022-05-31
Total Pages: 199
ISBN-13: 303179995X
DOWNLOAD EBOOKThis text presents a modern theory of analysis, control, and optimization for dynamic networks. Mathematical techniques of Lyapunov drift and Lyapunov optimization are developed and shown to enable constrained optimization of time averages in general stochastic systems. The focus is on communication and queueing systems, including wireless networks with time-varying channels, mobility, and randomly arriving traffic. A simple drift-plus-penalty framework is used to optimize time averages such as throughput, throughput-utility, power, and distortion. Explicit performance-delay tradeoffs are provided to illustrate the cost of approaching optimality. This theory is also applicable to problems in operations research and economics, where energy-efficient and profit-maximizing decisions must be made without knowing the future. Topics in the text include the following: - Queue stability theory - Backpressure, max-weight, and virtual queue methods - Primal-dual methods for non-convex stochastic utility maximization - Universal scheduling theory for arbitrary sample paths - Approximate and randomized scheduling theory - Optimization of renewal systems and Markov decision systems Detailed examples and numerous problem set questions are provided to reinforce the main concepts. Table of Contents: Introduction / Introduction to Queues / Dynamic Scheduling Example / Optimizing Time Averages / Optimizing Functions of Time Averages / Approximate Scheduling / Optimization of Renewal Systems / Conclusions
Author: Xiang-Sun Zhang
Publisher: Springer Science & Business Media
Published: 2013-03-09
Total Pages: 369
ISBN-13: 1475731671
DOWNLOAD EBOOKPeople are facing more and more NP-complete or NP-hard problems of a combinatorial nature and of a continuous nature in economic, military and management practice. There are two ways in which one can enhance the efficiency of searching for the solutions of these problems. The first is to improve the speed and memory capacity of hardware. We all have witnessed the computer industry's amazing achievements with hardware and software developments over the last twenty years. On one hand many computers, bought only a few years ago, are being sent to elementary schools for children to learn the ABC's of computing. On the other hand, with economic, scientific and military developments, it seems that the increase of intricacy and the size of newly arising problems have no end. We all realize then that the second way, to design good algorithms, will definitely compensate for the hardware limitations in the case of complicated problems. It is the collective and parallel computation property of artificial neural net works that has activated the enthusiasm of researchers in the field of computer science and applied mathematics. It is hard to say that artificial neural networks are solvers of the above-mentioned dilemma, but at least they throw some new light on the difficulties we face. We not only anticipate that there will be neural computers with intelligence but we also believe that the research results of artificial neural networks might lead to new algorithms on von Neumann's computers.
