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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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Negotiation mechanism for self-organized scheduling system with collective intelligence

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A variable neighborhood search based genetic algorithm for flexible job shop scheduling problem

TL;DR: To solve such an NP-hard problem, variable neighborhood search (VNS) based on genetic algorithm is proposed to enhance the search ability and to balance the intensification and diversification.
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New trends in constraint satisfaction, planning, and scheduling: a survey

TL;DR: This paper presents a survey on constraint satisfaction, planning, and scheduling from the Artificial Intelligence point of view, and presents the main definitions and techniques.
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A Pareto-based genetic algorithm for multi-objective scheduling of automated manufacturing systems:

TL;DR: A new Pareto-based genetic algorithm is proposed to solve multi-objective scheduling problems of automated manufacturing systems, which has limited resources and flexibility of processing routes of jobs, and hence is prone to deadlock.
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