Abstract

Preface. Introduction. 1: Elements of Graph Theory and Computational Complexity of Algorithms. 1. Sets, Orders, Graphs. 2. Balanced 2-3-Trees. 3. Polynomial Reducibility of Discrete Problems. Complexity of Algorithms. 4. Bibliography and Review. 2: Polynomially Solvable Problems. 1. Preemption. 2. Deadline-Feasible Schedules. 3. Single Machine. Maximal Cost. 4. Single Machine. Total Cost. 5. Identical Machines. Maximal Completion Time. Equal Processing Times. 6. Identical Machines. Maximal Completion Time. Preemption. 7. Identical Machines. Due Dates. Equal Processing Times. 8. Identical Machines. Maximal Lateness. 9. Uniform and Unrelated Parallel Machines. Total and Maximal Cost. 10. Bibliography and Review. 3: Priority-Generating Functions. Ordered Sets of Jobs. 1. Priority-Generating Functions. 2. Elimination Conditions. 3. Tree-like Order. 4. Series-Parallel Order. 5. General Case. 6. Convergence Conditions. 7. 1-Priority-Generating Functions. 8. Bibliography and Review. 4: NP-Hard Problems. 1. Reducibility of the Partition Problem. 2. Reducibility of the 3-Partition Problem. 3. Reducibility of the Vertex Covering Problem. 4. Reducibility of the Clique Problem. 5. Reducibility of the Linear Arrangement Problem. 6. Bibliographic Notes. Appendix. Approximation Algorithms. References. Additional References. Index.

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