Project planning, scheduling, and control are regularly used in business and the service sector of an economy to accomplish outcomes with limited resources under critical time constraints. To aid in solving these problems, network-based planning methods have been developed that now exist in a wide variety of forms, cf. Elmaghraby (1977) and Moder et al. (1983). The so-called "classical" project networks, which are used in the network techniques CPM and PERT and which represent acyclic weighted directed graphs, are able to describe only projects whose evolution in time is uniquely specified in advance. Here every event of the project is realized exactly once during a single project execution and it is not possible to return to activities previously carried out (that is, no feedback is permitted). Many practical projects, however, do not meet those conditions. Consider, for example, a production process where some parts produced by a machine may be poorly manufactured. If an inspection shows that a part does not conform to certain specifications, it must be repaired or replaced by a new item. This means that we have to return to a preceding stage of the production process. In other words, there is feedback. Note that the result of the inspection is that a certain percentage of the parts tested do not conform. That is, there is a positive probability (strictly less than 1) that any part is defective.

This book deals with dynamic and stochastic methods for multi-project planning. Based on the idea of using queueing networks for the analysis of dynamic-stochastic multi-project environments this book addresses two problems: detailed scheduling of project activities, and integrated order acceptance and capacity planning. In an extensive simulation study, the book thoroughly investigates existing scheduling policies. To obtain optimal and near optimal scheduling policies new models and algorithms are proposed based on the theory of Markov decision processes and Approximate Dynamic programming. Then the book presents a new model for the effective computation of optimal policies based on a Markov decision process. Finally, the book provides insights into the structure of optimal policies.

This multi-author volume, containing contributions from international experts in the field, presents recent developments in project scheduling for both theory and practice. It is organized in three parts: I. Basic deterministic models; II. Special deterministic models; III. Stochastic models. A variety of approaches is presented dealing with multiple-category resource constraints, different mathematical models of activities, and various project performance measures in single and multiobjective formulation. Exact and heuristic algorithms are presented for both deterministic and stochastic project description.The volume will be of special interest to scientists, students, decision makers, executive managers, consultants and practitioners involved in systems management or operations research, in particular in business, engineering, and finance, but also in other areas of pure and applied sciences.

This volume contains the proceedings of an Advanced Study and Re search Institute on Theoretical Approaches to Scheduling Problems. The Institute was held in Durham, England, from July 6 to July 17, 1981. It was attended by 91 participants from fifteen different countries. The format of the Institute was somewhat unusual. The first eight of the ten available days were devoted to an Advanced Study Insti tute, with lectures on the state of the art with respect to deter ministic and stochastic scheduling models and on the interface between these two approaches. The last two days were occupied by an Advanced Research Institute, where recent results and promising directions for future research, especially in the interface area, were discussed. Altogether, 37 lectures were delivered by 24 lecturers. They have all contributed to these proceedings, the first part of which deals with the Advanced Study Institute and the second part of which covers the Advanced Research Institute. Each part is preceded by an introduction, written by the editors. While confessing to a natural bias as organizers, we believe that the Institute has been a rewarding and enjoyable event for everyone concerned. We are very grateful to all those who have contributed to its realization.

This book is based on a graduate education program on computational discrete mathematics run for several years in Berlin, Germany, as a joint effort of theoretical computer scientists and mathematicians in order to support doctoral students and advanced ongoing education in the field of discrete mathematics and algorithmics. The 12 selected lectures by leading researchers presented in this book provide recent research results and advanced topics in a coherent and consolidated way. Among the areas covered are combinatorics, graph theory, coding theory, discrete and computational geometry, optimization, and algorithmic aspects of algebra.

The 5th Symposium on Stochastic Algorithms, Foundations and Applications (SAGA 2009) took place during October 26–28, 2009, at Hokkaido University, Sapporo(Japan).ThesymposiumwasorganizedbytheDivisionofComputerS- ence,GraduateSchoolofComputerScienceandTechnology,HokkaidoUniversity. It o?ered the opportunity to present original research on the design and analysis of randomized algorithms, random combinatorialstructures, implem- tation, experimental evaluation and real-world application of stochastic al- rithms/heuristics. In particular, the focus of the SAGA symposia series is on investigating the power of randomization in algorithms, and on the theory of stochastic processes especially within realistic scenarios and applications. Thus, the scope ofthe symposiumrangesfromthe study oftheoreticalfundamentals of randomizedcomputationtoexperimentalinvestigationsonalgorithms/heuristics and related stochastic processes. The SAGA symposium series is a biennial meeting. Previous SAGA s- posiatookplaceinBerlin,Germany(2001,LNCSvol.2264),Hat?eld,UK(2003, LNCS vol. 2827), Moscow, Russia (2005, LNCS vol. 3777), and Zur ¨ ich, Switz- land (2007, LNCS vol. 4665). This year 22 submissions were received, and the Program Committee selected 15 submissions for presentation. All papers were evaluated by at least three members of the ProgramCommittee, partly with the assistance of subreferees. The present volume contains the texts of the 15 papers presented at SAGA 2009, divided into groups of papers on learning, graphs, testing, optimization, and caching as well as on stochastic algorithms in bioinformatics.

A comprehensive guide to the concepts and applications of queuing theory and traffic theory Network Traffic Engineering: Models and Applications provides an advanced level queuing theory guide for students with a strong mathematical background who are interested in analytic modeling and performance assessment of communication networks. The text begins with the basics of queueing theory before moving on to more advanced levels. The topics covered in the book are derived from the most cutting-edge research, project development, teaching activity, and discussions on the subject. They include applications of queuing and traffic theory in: LTE networks Wi-Fi networks Ad-hoc networks Automated vehicles Congestion control on the Internet The distinguished author seeks to show how insight into practical and real-world problems can be gained by means of quantitative modeling. Perfect for graduate students of computer engineering, computer science, telecommunication engineering, and electrical engineering, Network Traffic Engineering offers a supremely practical approach to a rapidly developing field of study and industry.

This book constitutes the refereed proceedings of the Third International Workshop on Approximation Algorithms for Combinatorial Optimization Problems, APPROX 2000, held in Saarbrücken, Germany in September 2000. The 22 revised full papers presented together with four invited contributions were carefully reviewed and selected from 68 submissions. The topics dealt with include design and analysis of approximation algorithms, inapproximibility results, on-line problems, randomization techniques, average-case analysis, approximation classes, scheduling problems, routing and flow problems, coloring and partitioning, cuts and connectivity, packing and covering, geometric problems, network design, and various applications.