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Metaheuristics for Scheduling in Industrial and Manufacturing Applications (Hardcover, 2008 ed.)
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Metaheuristics for Scheduling in Industrial and Manufacturing Applications (Hardcover, 2008 ed.)
Series: Studies in Computational Intelligence, 128
Expected to ship within 12 - 17 working days
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During the past decades scheduling has been among the most studied
op- mization
problemsanditisstillanactiveareaofresearch!Schedulingappears in
many areas of science, engineering and industry and takes di?erent
forms depending on the restrictions and optimization criteria of
the operating en- ronments [8]. For instance, in optimization and
computer science, scheduling has been de?ned as "the allocation of
tasks to resources over time in order to achieve optimality in one
or more objective criteria in an e?cient way" and in production as
"production schedule, i. e. , the planning of the production or the
sequence of operations according to which jobs pass through
machines and is optimal with respect to certain optimization
criteria. " Although there is a standardized form of stating any
scheduling problem, namely "e?cient allocation ofn jobs onm
machines -which can process no more than one activity at a time-
with the objective to optimize some - jective function of the job
completion times", scheduling is in fact a family of problems.
Indeed, several parameters intervene in the problem de?nition: (a)
job characteristics (preemptive or not, precedence constraints,
release dates, etc. ); (b) resource environment (single vs.
parallel machines, un- lated machines, identical or uniform
machines, etc. ); (c) optimization criteria (minimize total
tardiness, the number of late jobs, makespan, ?owtime, etc. ;
maximize resource utilization, etc. ); and, (d) scheduling
environment (static vs.
dynamic,intheformerthenumberofjobstobeconsideredandtheirready times
are available while in the later the number of jobs and their
charact- istics change over time).
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