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Scheduling: Theory, Algorithms, and Systems

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TLDR
Scheduling will serve as an essential reference for professionals working on scheduling problems in manufacturing and computing environments and Graduate students in operations management, operations research, industrial engineering and computer science will find the book to be an accessible and invaluable resource.
Abstract
This book on scheduling covers theoretical models as well as scheduling problems in the real world. Author Michael Pinedo also includes a CD that contains slide-shows from industry and movies dealing with implementations of scheduling systems. The book consists of three parts. The first part focuses on deterministic scheduling with the associated combinatorial problems. The second part covers probabilistic scheduling models. In this part it is assumed that processing times and other problem data are not known in advance. The third part deals with scheduling in practice. It covers heuristics that are popular with practitioners and discusses system design and development issues. Each chapter contains a series of computational and theoretical exercises. This book is of interest to theoreticians and practitioners alike. Graduate students in operations management, operations research, industrial engineering and computer science will find the book to be an accessible and invaluable resource. Scheduling will serve as an essential reference for professionals working on scheduling problems in manufacturing and computing environments. Michael Pinedo is the Julius Schlesinger Professor of Operations Management at New York University.

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BookDOI

Metaheuristic Optimization via Memory and Evolution

TL;DR: It is illustrated how scatter search can be effectively used for the solution of general permutation problems that involve the determination of optimal cycles (or circuits) in graph theory and combinatorial optimization.
Proceedings ArticleDOI

A scheduling approach to coalitional manipulation

TL;DR: This paper solves the coalitional manipulation problem under the important family of positional scoring rules, in an approximate sense, with the following theoretical guarantee: given a manipulable instance with m alternatives, the algorithm finds a successful manipulation with at most m - 2 additional manipulators.
Journal ArticleDOI

Simultaneous Job Scheduling and Resource Allocation on Parallel Machines

TL;DR: This paper studies a parallel-machine scheduling model involving both job processing and resource allocation and develops a column generation based branch and bound method for finding optimal solutions for these NP-hard problems.
Journal ArticleDOI

The complexity of machine scheduling for stability with a single disrupted job

TL;DR: The purpose of this paper is to investigate the complexity status of a number of machine scheduling problems with stability objective when the duration of a single job is anticipated to be disrupted.
Journal ArticleDOI

Benchmark-problem instances for static scheduling of task graphs with communication delays on homogeneous multiprocessor systems

TL;DR: This work proposes test-problem instances for the MSPCD that are representative in terms of number of processors, type of multiprocessor architecture, number of tasks to be scheduled, and task graph characteristics (task execution times, communication costs, and density of dependencies between tasks).
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