The chapter "Sequencing and Scheduling: Algorithms and Complexity" by Lawler, Lenstra, Rinnooy Kan, and Shmoys provides a comprehensive overview of the field of sequencing and scheduling, focusing on deterministic machine scheduling. The authors introduce the fundamental concepts and classification of scheduling problems, including the types of resources, machine environments, job characteristics, and optimality criteria. They discuss the complexity of various scheduling problems, highlighting both polynomial-time solvable cases and NP-hard problems. The chapter is organized into several sections, each addressing specific aspects of scheduling, such as single-machine scheduling, parallel-machine scheduling, and multi-operation models. It also covers extensions like resource-constrained project scheduling and stochastic machine scheduling. The authors provide detailed algorithms and complexity analyses for various scheduling problems, including those involving minimizing maximum lateness, total weighted completion time, and weighted number of late jobs. The chapter emphasizes the importance of understanding the complexity of scheduling problems and the development of efficient algorithms for practical applications.The chapter "Sequencing and Scheduling: Algorithms and Complexity" by Lawler, Lenstra, Rinnooy Kan, and Shmoys provides a comprehensive overview of the field of sequencing and scheduling, focusing on deterministic machine scheduling. The authors introduce the fundamental concepts and classification of scheduling problems, including the types of resources, machine environments, job characteristics, and optimality criteria. They discuss the complexity of various scheduling problems, highlighting both polynomial-time solvable cases and NP-hard problems. The chapter is organized into several sections, each addressing specific aspects of scheduling, such as single-machine scheduling, parallel-machine scheduling, and multi-operation models. It also covers extensions like resource-constrained project scheduling and stochastic machine scheduling. The authors provide detailed algorithms and complexity analyses for various scheduling problems, including those involving minimizing maximum lateness, total weighted completion time, and weighted number of late jobs. The chapter emphasizes the importance of understanding the complexity of scheduling problems and the development of efficient algorithms for practical applications.