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Scheduling with Time-Changing Effects and Rate-Modifying Activities (Paperback, Softcover reprint of the original 1st ed. 2017)
Loot Price: R4,300
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Scheduling with Time-Changing Effects and Rate-Modifying Activities (Paperback, Softcover reprint of the original 1st ed. 2017)
Series: International Series in Operations Research & Management Science, 243
Expected to ship within 10 - 15 working days
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In scheduling theory, the models that have attracted considerable
attention during the last two decades allow the processing times to
be variable, i.e., to be subjected to various effects that make the
actual processing time of a job dependent on its location in a
schedule. The impact of these effects includes, but is not limited
to, deterioration and learning. Under the first type of effect, the
later a job is scheduled, the longer its actual processing time
becomes. In the case of learning, delaying a job will result in
shorter processing times. Scheduling with Time-Changing Effects and
Rate-Modifying Activities covers and advances the state-of-the-art
research in this area. The book focuses on single machine and
parallel machine scheduling problems to minimize either the maximum
completion time or the sum of completion times of all jobs,
provided that the processing times are subject to various effects.
Models that describe deterioration, learning and general
non-monotone effects to be considered include positional,
start-time dependent, cumulative and their combinations, which
cover most of the traditionally used models. The authors also
consider more enhanced models in which the decision-maker may
insert certain Rate-Modifying Activities (RMA) on processing
machines, such as for example, maintenance or rest periods. In any
case, the processing times of jobs are not only dependent on
effects mentioned above but also on the place of a job in a
schedule relative to an RMA. For most of the enhanced models
described in the book, polynomial-time algorithms are presented
which are based on similar algorithmic ideas such as reduction to
linear assignment problems (in a full form or in a reduced form),
discrete convexity, and controlled generation of options.
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