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CHAPTER ONE INTRODUCTION
CHAPTER TWO ALGORITHMS
CHAPTER THREE SCHEDULING ALGORITHMS
6 other sections not shown
3-satisfiability Algorithm 2.2 approximate algorithms arbitrary AS/DB assigned assume bound branch-and-bound algorithm branching node Chapter complete solution computational requirements consider constructed deadline defined denote dynamic programming elements example FIFO Figure finishing flow pattern flow-shop problem follows G BFST given graph heuristics identical processors idle immediate successor independent tasks input integer job-shop problem job-system knapsack problem labeling Lemma list schedule mean weighted flow minimal minimal-length schedule mwft neighborhood nonpreemptive schedule NP-complete number of processors optimal permutation optimal schedule optimal solution p-maximal set parameters partial order partial solutions polynomial precedence constraints preemptions preemptive schedule Proof random variable resource respect to 9 schedule for 2T schedule length scheduling problem scheduling rule scheduling theory sequencing problems set with respect subset Suppose task system tasks executed terminal Theorem traveling salesman problem tree U/DBAS UET scheduling unit upper-bound solution variables