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Systems Science
Queueing Theory and Scheduling
1. Introduction to Queueing Systems
2. Mathematical Foundations
3. Basic Markovian Queueing Models
4. Advanced Queueing Models
5. Queueing Networks
6. Fundamentals of Scheduling
7. Single Machine Scheduling
8. Parallel Machine Scheduling
9. Flow Shop and Job Shop Scheduling
10. Real-Time Scheduling
11. Network Scheduling
12. Analysis Techniques and Tools
13. Performance Evaluation and Optimization
14. Applications and Case Studies
6.
Fundamentals of Scheduling
6.1.
Introduction to Scheduling
6.1.1.
Definition and Scope
6.1.2.
Relationship to Queueing Theory
6.1.3.
Decision Variables
6.1.4.
Constraints
6.2.
Scheduling Objectives
6.2.1.
Completion Time Criteria
6.2.1.1.
Makespan
6.2.1.2.
Total Completion Time
6.2.1.3.
Mean Flow Time
6.2.2.
Due Date Criteria
6.2.2.1.
Maximum Lateness
6.2.2.2.
Total Tardiness
6.2.2.3.
Number of Tardy Jobs
6.2.3.
Inventory and Cost Criteria
6.2.3.1.
Holding Costs
6.2.3.2.
Setup Costs
6.2.3.3.
Penalty Costs
6.2.4.
Fairness Criteria
6.2.4.1.
Variance of Completion Times
6.2.4.2.
Range of Completion Times
6.2.5.
Multi-Objective Scheduling
6.3.
Problem Classification
6.3.1.
Machine Environment
6.3.1.1.
Single Machine
6.3.1.2.
Parallel Machines
6.3.1.3.
Flow Shop
6.3.1.4.
Job Shop
6.3.1.5.
Open Shop
6.3.2.
Job Characteristics
6.3.2.1.
Processing Times
6.3.2.2.
Release Times
6.3.2.3.
Due Dates
6.3.2.4.
Precedence Constraints
6.3.3.
Scheduling Constraints
6.3.3.1.
Preemption
6.3.3.2.
Setup Times
6.3.3.3.
Resource Constraints
6.3.4.
Information Availability
6.3.4.1.
Static vs Dynamic
6.3.4.2.
Deterministic vs Stochastic
6.3.4.3.
Online vs Offline
6.4.
Graham's Notation
6.4.1.
Machine Environment (α)
6.4.2.
Job Characteristics (β)
6.4.3.
Optimality Criterion (γ)
6.4.4.
Common Problem Types
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7. Single Machine Scheduling