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This book presents multi-agent scheduling models in which subsets of jobs sharing the same resources are evaluated by different criteria. It discusses complexity results, approximation schemes, heuristics and exact algorithms.

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Scheduling theory has received a growing interest since its origins in the second half of the 20th century. Developed initially for the study of scheduling problems with a single objective, the theory has been recently extended to problems involving multiple criteria. However, this extension has still left a gap between the classical multi-criteria approaches and some real-life problems in which not all jobs contribute to the evaluation of each criterion.

In this book, we close this gap by presenting and developing multi-agent scheduling models in which subsets of jobs sharing the same resources are evaluated by different criteria. Several scenarios are introduced, depending on the definition and the intersection structure of the job subsets. Complexity results, approximation schemes, heuristics and exact algorithms are discussed for single-machine and parallel-machine scheduling environments. Definitions and algorithms are illustrated with the help of examples and figures.

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1. Multiagent Scheduling Fundamentals.- 2. Problems, Algorithms and Complexity.- 3. Single Machine Problems.- 4. Batching Scheduling Problems.- 5. Parallel Machine Scheduling Problems.- 6. Scheduling Problems with Variable Job Processing Times.- References.

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"It is very readable and precisely written. The major results are proved and 43 algorithmic descriptions are provided. The book contains also several numerical examples to illustrate the presented solution approaches. The book is recommended not only for researchers and practitioners working in scheduling, but also for graduate students since only basic knowledge in discrete mathematics, complexity theory, algorithms, and programming languages is required." (Frank Werner, Mathematical Reviews, May, 2017)

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