2 research outputs found
Efficient local search limitation strategy for single machine total weighted tardiness scheduling with sequence-dependent setup times
This paper concerns the single machine total weighted tardiness scheduling
with sequence-dependent setup times, usually referred as . In this -hard problem, each job has an associated
processing time, due date and a weight. For each pair of jobs and ,
there may be a setup time before starting to process in case this job is
scheduled immediately after . The objective is to determine a schedule that
minimizes the total weighted tardiness, where the tardiness of a job is equal
to its completion time minus its due date, in case the job is completely
processed only after its due date, and is equal to zero otherwise. Due to its
complexity, this problem is most commonly solved by heuristics. The aim of this
work is to develop a simple yet effective limitation strategy that speeds up
the local search procedure without a significant loss in the solution quality.
Such strategy consists of a filtering mechanism that prevents unpromising moves
to be evaluated. The proposed strategy has been embedded in a local search
based metaheuristic from the literature and tested in classical benchmark
instances. Computational experiments revealed that the limitation strategy
enabled the metaheuristic to be extremely competitive when compared to other
algorithms from the literature, since it allowed the use of a large number of
neighborhood structures without a significant increase in the CPU time and,
consequently, high quality solutions could be achieved in a matter of seconds.
In addition, we analyzed the effectiveness of the proposed strategy in two
other well-known metaheuristics. Further experiments were also carried out on
benchmark instances of problem .Comment: 32 pages, 4 figure
A unified heuristic and an annotated bibliography for a large class of earliness-tardiness scheduling problems
This work proposes a unified heuristic algorithm for a large class of
earliness-tardiness (E-T) scheduling problems. We consider single/parallel
machine E-T problems that may or may not consider some additional features such
as idle time, setup times and release dates. In addition, we also consider
those problems whose objective is to minimize either the total (average)
weighted completion time or the total (average) weighted flow time, which arise
as particular cases when the due dates of all jobs are either set to zero or to
their associated release dates, respectively. The developed local search based
metaheuristic framework is quite simple, but at the same time relies on
sophisticated procedures for efficiently performing local search according to
the characteristics of the problem. We present efficient move evaluation
approaches for some parallel machine problems that generalize the existing ones
for single machine problems. The algorithm was tested in hundreds of instances
of several E-T problems and particular cases. The results obtained show that
our unified heuristic is capable of producing high quality solutions when
compared to the best ones available in the literature that were obtained by
specific methods. Moreover, we provide an extensive annotated bibliography on
the problems related to those considered in this work, where we not only
indicate the approach(es) used in each publication, but we also point out the
characteristics of the problem(s) considered. Beyond that, we classify the
existing methods in different categories so as to have a better idea of the
popularity of each type of solution procedure