• The Journal of Bigdata
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• v.5 no.1
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• pp.189-195
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• 2020

We consider the stale problem which makes the training speed slow in the field of deep learning. The problem can be formulated as a single-machine scheduling problem with generalized due dates in which the objective is to minimize the total earliness and tardiness. We show that the problem can be solved in polynomial time if the orders of the small and the large jobs in an optimal schedule are known in advance.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.31 no.4
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• pp.1-9
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• 2008

JIT 생산시스템이 세계적으로 많은 회사에 적용됨에 따라 earliness와 tardiness의 페널티를 동시에 최소화하는 문제에 대한 많은 연구가 진행되어 왔다. 이 연구에서는 한정된 완료시간의 편차에 대해서는 페널티를 부과하지 않는, 즉 허용오차가 존재할 때, 공통의 납기로부터 평균제곱편차(MSD : Mean Squared Deviation)를 최소화하는 단일기계 문제를 다룬다. 허용오차가 존재하는 MSD 문제에서 최적의 공통 납기를 결정하는 방법을 개발한다. 스케줄과 허용 오차가 주어질 때, 최적의 납기를 찾는 두 개의 선형시간이 소요되는 알고리즘을 제시한다. 주어진 허용오차 중 하나는 가장 짧은 가공시간을 가지는 작업의 절반보다 작은 경우이며 다른 하나는 허용오차가 임의인 경우이다.

• Proceedings of the Korea Contents Association Conference
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• 2018.05a
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• pp.501-502
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• 2018

ICT기술은 소프트웨어와 하드웨어의 모든 분야에서 비약적으로 발전을 거듭하고 있다. 이에 따라, 기업에서 전통적으로 사용되어 오는 경영정보시스템들도 다양한 형태로 개선되거나 융합되어지고 있다. 특히, 재택근무, 이동근무, 원격 협업 등의 ICT기술 활용하여 시간과 장소에 얽매이지 않고 업무를 수행하는 스마트워크는 기업의 근무행태에 대한 패러다임을 바꿀 것으로 기대를 받고 있다. 본 논문에서는 이러한 스마트워크의 일환으로 BLE(Bluetooth Low Energy Beacon)을 이용한 모바일 형태의 그룹웨어 시스템을 제안한다.

• Journal of Korean Institute of Industrial Engineers
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• v.27 no.2
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• pp.158-168
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• 2001

We present a tabu search (TS) algorithm to minimize maximum lateness on a single machine in the presence of sequence dependent setup times and dynamic job arrivals. The TS algorithm starts with a feasible schedule generated by a modified ATCS (Apparent Tardiness Cost with Setups) rule, then through a series of search steps it improves the initial schedule. Results of extensive computational experiments show that the TS algorithm significantly outperforms a well-known RHP heuristic by Ovacik and Uzsoy, both on the solutions quality and the computation time. The performance advantage is particularly pronounced when there is high competition among jobs for machine capacity.

• Journal of Korean Institute of Industrial Engineers
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• v.24 no.3
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• pp.345-357
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• 1998

This paper focuses on production planning and scheduling problems in an assembly system operating on a make-to-order basis. Due dates are considered as constraints in the problems, that is, tardiness is not allowed. Since the planning problem is a higher-level decision making than the scheduling problem, the scheduling problem is solved using a production plan obtained by solving the planning problem. We suggest heuristic procedures in which aggregated information is used when the production planning problem is solved while more detailed information is used when the scheduling problem is solved. Since a feasible schedule may not be obtained from a production plan, an iterative approach is employed in the two procedures to obtain a solution that is feasible for both the production planning and scheduling problems. Computational tests on randomly generated test problems are done to show the performance of these algorithms, and results are reported.

• Journal of Korean Institute of Industrial Engineers
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• v.33 no.3
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• pp.329-338
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• 2007

This paper presents a dispatching algorithm for nonidentical parallel machines problem considering rework, sequence dependent setup times and release times. For each pair of a machine and a job type, rework probability of each job on a machine can be known through historical data acquisition. The heuristic scheduling scheme named by EDDR (Earliest Due Date with Rework probability) algorithm is proposed in this paper making use of the rework probability. The proposed dispatching algorithm is measured by two objective function value: 1) total tardiness and 2) the number of reworked jobs, respectively. The extensive computational results show that the proposed algorithm gives very efficient schedules superior to the existing dispatching algorithms.

• Journal of the Korean Wood Science and Technology
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• v.21 no.2
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• pp.23-30
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• 1993

As the demand of wood furniture becomes diverse and large-sized, artificial intelligence technique is required to design the expert system which can promote the efficiency of the operations management in wood furniture industry. This study was carried out to develop the expert scheduler, which was applied to the scheduling in chair-manufacturing process to evaluate its validity. The expert scheduler could show the results of scheduling must faster than Gantt chart method with ease. Maximum tardiness in the current chair-manufacturing process could be reduced from 29 seconds to 5 seconds by the addition of a spindle sander, a 12 spindle universal boring machine, and a moulding sander to sanding, boring, and moulding process, respectively.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 1997.03a
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• pp.209-222
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• 1997

생산시스템에 있어서 스케쥴링 문제에 관한 이론적 연구는 종래부터 많이 연구되어 왔지만, 그 대부분은 작업의 가공시간이 확정적(deterministic)인 경우의 평가척도(criterion)를 고려한 것이었다. 그러나 실제 노동집약형 산업이라든가 고장율이 높은 자동화 공장등에 있어서는 가공시간 또는 제조 리드타임이 확률적인 변동을 갖는 경우가 많다. 이러한 가공시간의 변동은 각 작업의 가공완료시각의 변동으로 되어 후공정의 작업계획에 중대한 영향을 미치게 된다. 따라서 가공시간이 확률적(probabilistic)인 경우의 생산 시스템을 대상으로 한 스케쥴링 문제에 관한 연구는 최근에 와서 연구되고 있는 실정이다. 본 연구에서는 종래의 단일 공정의 생산 시스템을 대상으로 n개의 작업이 확정적인 가공시간을 갖는 경우의 총체류시간(total flow time)과 납기(due date)의 평가척도에 관한 스케쥴링 문제를 가공시간이 확률적인 분포를 갖는 경우로 확장시킨 스케쥴링 문제를 제안한다. 그리고 납기에 있어서 평균 납기지연확률(mean probability of tardiness)을 최소화하는 스케쥴링 문제의 휴리스틱 해법을 제안하여 그 실용성을 검토하였다.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.19 no.39
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• pp.275-284
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• 1996

It can be made a definition that scheduling is a imposition of machinery and equipment to perform a collection of tasks. Ultimately scheduling is an assessment of taking order for which would be perform. So it is called "sequencing" in other words. In a job shop scheduling, the main object is to making delivery in accordance with the due date and order form customer, not to producing lots of quantity with minimizing mean flow time in a given time. Actually, in a company, they concentrate more in the delivery than minimizing the mean flow time. Therefore this paper suggest a new priority dispatching rule under consideration as below in a n/m job shop scheduling problem with due date. 1. handling/transportation time, 2. the size of customer order With this algorithm, we can make a scheduling for minimizing the tardiness of delivery which satisfy a goal of production.roduction.

• International Journal of Computer Science & Network Security
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• v.22 no.8
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• pp.45-54
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• 2022

In this study, a multi-objective robust job-shop scheduling (JSS) model was developed. The model considered multi-jobs and multi-machines. The model also considered uncertain processing times for all tasks. Each job was assigned a specific due date and a tardiness penalty to be paid if the job was not delivered on time. If any job was completed early, holding expenses would be assigned. In addition, the model added idling penalties to accommodate the idling of machines while waiting for jobs. The problem assigned was to determine the optimal start times for each task that would minimize the expected penalties. A numerical problem was solved to minimize both the makespan and the total penalties, and a comparison was made between the results. Analysis of the results produced a prescription for optimizing penalties that is important to be accounted for in conjunction with uncertainties in the job-shop scheduling problem (JSSP).