Scheduling: theory, algorithms, and systems
This comprehensive book focuses on the theory and applications of scheduling. Applications are primarily drawn from production and manufacturing environments, but state principles relevant to other settings as well. Includes numerous worked out examples, Deterministic Models, Stochastic Models, Applications, and more. For anyone interested in scheduling, project management, production planning, and inventory control.
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Single Machine Models Deterministic
MORE ADVANCED SINGLE MACHINE MODELS
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algorithm applied beam search branch and bound Class 1 jobs class of nonpreemptive Cmax computed CP rule denote described determined deterministic disjunctive arcs distributed with rate due date dynamic programming equal Example expected makespan exponentially distributed Figure flexible flow flow shops Gantt chart genetic algorithms Gittins index graph heuristic instance interface Lemma Lmax lower bound LRPT machine environment machines in parallel minimizes the expected minimizes the total models node nonpreemptive static list number of jobs number of machines objective function operation optimal schedule optimal sequence pairwise interchange parallel machine permutation Pinedo polynomial precedence constraints preemptions preemptive dynamic policies priority prmp procedure processed on machine proof queue random variable release dates remaining processing scheduling problems scheduling systems set of jobs setup simulated annealing single machine solution static list policies stochastic dominance strongly NP-hard Theorem three jobs total completion total weighted tardiness Traveling Salesman Problem WSPT zero