18,878 research outputs found
Parameterized complexity of machine scheduling: 15 open problems
Machine scheduling problems are a long-time key domain of algorithms and
complexity research. A novel approach to machine scheduling problems are
fixed-parameter algorithms. To stimulate this thriving research direction, we
propose 15 open questions in this area whose resolution we expect to lead to
the discovery of new approaches and techniques both in scheduling and
parameterized complexity theory.Comment: Version accepted to Computers & Operations Researc
Dynamic scheduling in a multi-product manufacturing system
To remain competitive in global marketplace, manufacturing companies need to improve their operational practices. One of the methods to increase competitiveness in manufacturing is by implementing proper scheduling system. This is important to enable job orders to be completed on time, minimize waiting time and maximize utilization of equipment and machineries. The dynamics of real manufacturing system are very complex in nature. Schedules developed based on deterministic algorithms are unable to effectively deal with uncertainties in demand and capacity. Significant differences can be found between planned schedules and actual schedule implementation. This study attempted to develop a scheduling system that is able to react quickly and reliably for accommodating changes in product demand and manufacturing capacity. A case study, 6 by 6 job shop scheduling problem was adapted with uncertainty elements added to the data sets. A simulation model was designed and implemented using ARENA simulation package to generate various job shop scheduling scenarios. Their performances were evaluated using scheduling rules, namely, first-in-first-out (FIFO), earliest due date (EDD), and shortest processing time (SPT). An artificial neural network (ANN) model was developed and trained using various scheduling scenarios generated by ARENA simulation. The experimental results suggest that the ANN scheduling model can provided moderately reliable prediction results for limited scenarios when predicting the number completed jobs, maximum flowtime, average machine utilization, and average length of queue. This study has provided better understanding on the effects of changes in demand and capacity on the job shop schedules. Areas for further study includes: (i) Fine tune the proposed ANN scheduling model (ii) Consider more variety of job shop environment (iii) Incorporate an expert system for interpretation of results. The theoretical framework proposed in this study can be used as a basis for further investigation
Flow shop scheduling with earliness, tardiness and intermediate inventory holding costs
We consider the problem of scheduling customer orders in a flow shop with the objective of minimizing the sum of tardiness, earliness (finished goods inventory holding) and intermediate (work-in-process) inventory holding costs. We formulate this problem as an integer program, and based on approximate solutions to two di erent, but closely related, Dantzig-Wolfe reformulations, we develop heuristics to minimize the total cost. We exploit the duality between Dantzig-Wolfe reformulation and Lagrangian relaxation to enhance our heuristics. This combined approach enables us to develop two di erent lower bounds on the optimal integer solution, together with intuitive approaches for obtaining near-optimal feasible integer solutions. To the best of our knowledge, this is the first paper that applies column generation to a scheduling problem with di erent types of strongly NP-hard pricing problems which are solved heuristically. The computational study demonstrates that our algorithms have a significant speed advantage over alternate methods, yield good lower bounds, and generate near-optimal feasible integer solutions for problem instances with many machines and a realistically large number of jobs
The Complexity of Mean Flow Time Scheduling Problems with Release Times
We study the problem of preemptive scheduling n jobs with given release times
on m identical parallel machines. The objective is to minimize the average flow
time. We show that when all jobs have equal processing times then the problem
can be solved in polynomial time using linear programming. Our algorithm can
also be applied to the open-shop problem with release times and unit processing
times. For the general case (when processing times are arbitrary), we show that
the problem is unary NP-hard.Comment: Subsumes and replaces cs.DS/0412094 and "Complexity of mean flow time
scheduling problems with release dates" by P.B, S.
A linear programming-based method for job shop scheduling
We present a decomposition heuristic for a large class of job shop scheduling problems. This heuristic utilizes information from the linear programming formulation of the associated optimal timing problem to solve subproblems, can be used for any objective function whose associated optimal timing problem can be expressed as a linear program (LP), and is particularly effective for objectives that include a component that is a function of individual operation
completion times. Using the proposed heuristic framework, we address job shop scheduling problems with a variety of objectives where intermediate holding costs need to be explicitly considered. In computational testing, we demonstrate the performance of our proposed solution approach
A scheduling theory framework for GPU tasks efficient execution
Concurrent execution of tasks in GPUs can reduce the computation time of a workload by
overlapping data transfer and execution commands.
However it is difficult to implement an efficient run-
time scheduler that minimizes the workload makespan
as many execution orderings should be evaluated. In
this paper, we employ scheduling theory to build a
model that takes into account the device capabili-
ties, workload characteristics, constraints and objec-
tive functions. In our model, GPU tasks schedul-
ing is reformulated as a flow shop scheduling prob-
lem, which allow us to apply and compare well known
methods already developed in the operations research
field. In addition we develop a new heuristic, specif-
ically focused on executing GPU commands, that
achieves better scheduling results than previous tech-
niques. Finally, a comprehensive evaluation, showing
the suitability and robustness of this new approach,
is conducted in three different NVIDIA architectures
(Kepler, Maxwell and Pascal).Proyecto TIN2016- 0920R, Universidad de Málaga (Campus de Excelencia Internacional Andalucía Tech) y programa de donación de NVIDIA Corporation
A generic method for energy-efficient and energy-cost-effective production at the unit process level
Framework for sustainable TVET-Teacher Education Program in Malaysia Public Universities
Studies had stated that less attention was given to the education aspect, such as
teaching and learning in planning for improving the TVET system. Due to the 21st
Century context, the current paradigm of teaching for the TVET educators also has
been reported to be fatal and need to be shifted. All these disadvantages reported
hindering the country from achieving the 5th strategy in the Strategic Plan for
Vocational Education Transformation to transform TVET system as a whole.
Therefore, this study aims to develop a framework for sustainable TVET Teacher
Education program in Malaysia. This study had adopted an Exploratory Sequential
Mix-Method design, which involves a semi-structured interview (phase one) and
survey method (phase two). Nine experts had involved in phase one chosen by using
Purposive Sampling Technique. As in phase two, 118 TVET-TE program lecturers
were selected as the survey sample chosen through random sampling method. After
data analysis in phase one (thematic analysis) and phase two (Principal Component
Analysis), eight domains and 22 elements have been identified for the framework for
sustainable TVET-TE program in Malaysia. This framework was identified to embed
the elements of 21st Century Education, thus filling the gap in this research. The
research findings also indicate that the developed framework was unidimensional and
valid for the development and research regarding TVET-TE program in Malaysia.
Lastly, it is in the hope that this research can be a guide for the nations in producing a
quality TVET teacher in the future
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