Scheduling: Theory, Algorithms, and SystemsDealing primarily with machine scheduling models, this three-part approach covers deterministic models, stochastic models and applications in the real world. |
Contents
INTRODUCTION | 1 |
PRELIMINARIES | 8 |
SINGLE MACHINE MODELS DETERMINISTIC | 26 |
Copyright | |
15 other sections not shown
Common terms and phrases
algorithm assignment bottleneck class of nonpreemptive Cmax computed Consider CP rule denote determined deterministic directed graph dispatching rule distributed with rate due dates dynamic programming equal Example expected makespan exponentially distributed flexible flow flow shop flow shops Gantt chart Gittins index graph heuristic idle integer integer programming intermediate storage Lemma LEPT Lmax lower bound LP relaxation LRPT machine environment machines in parallel minimizes the expected minimizes the makespan models node nonpreemptive dynamic policies nonpreemptive static list number of jobs number of machines Operations Research optimal schedule optimal sequence pairwise interchange permutation Pinedo polynomial precedence constraints preemptions preemptive dynamic policies priority prmp procedure processed on machine proof random variable release dates remaining jobs remaining processing scheduling problems scheduling systems setup simulated annealing single machine stage static list policies stochastic dominance Stochastic Scheduling strongly NP-hard tardiness Theorem three jobs WSPT zero λι