• 한국컴퓨터산업학회논문지
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• 제6권5호
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• pp.813-820
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• 2005

대체공정을 고려한 Job Shop 일정계획을 수립하기 위한 유전알고리즘을 개발하기 위하여 다음과 같이 유전알고리즘 효율분석을 실시하였다. 첫째, 대체공정을 고려한 job shop 일정계획을 수립하기 위한 유전 알고리즘을 제시하고 둘째, 전통적인 job shop 일정계획에 대한 벤치마크 문제에 대해 유전 알고리즘의 타당성을 확인하고 셋째, Park[3] 문제에 대해 유전알고리즘과 작업배정규칙을 적용한 결과를 비교하였다.

• International Journal of Computer Science & Network Security
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• 제22권8호
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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).

• 한국지능시스템학회논문지
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• 제11권3호
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• pp.191-199
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• 2001

유전자알고리듬(Genetic Algorithm)은 확률적인 집단 탐색법이고 적응도함수의 형태에 관계없는 직접 탐색법이기 때문에 최근 최적화 방법으로 주목을 받고 있다. 본 논문에서는 Job-shop Schedule Problem에 대하여 교배방법으로 JOX를 사용하며, 효율적인 탐색을 위하여 탐색범위를 축소시키는 강제조작을 형질유전을 고려한 형질유전GT법을 제안하고, 세대교체에 있어 모집단의 다양성을 유지하기 위하여 집단 내에 동일한 개체를 배제하는 방법을 제안한다. 제안 알고리듬을 Fisher & Thompson의 FT10$\times$10 및 FT20$\times$5 문제에 적용하여 유효성을 실험적으로 검증한다.

• 산업경영시스템학회지
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• 제19권39호
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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.

• 한국경영과학회지
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• 제30권3호
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• pp.55-65
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• 2005

In recent manufacturing systems, most jobs may have several process plans, such as alternative sequence of operations, alternative machine etc. A few researches have addressed the necessity for the integration of process planning and scheduling function for efficient use of manufacturing resources. But the integration problem is very difficult and complex. Many prior researches considered them separately or sequentially. It introduces overlapping or partial duplications in solution efforts. In this paper, Integration problem of jobs with multiple process plans in a job shop environment Is addressed. In order to achieve an efficient integration between process planning and scheduling by taking advantage of the flexibility that alternative process plans offer, we designed GA(Genetic Algorithm)-based scheduling method. The performance of proposed GA is evaluated through comparing integrated scheduling with separated scheduling in real world company with alternative machines and sequences of operations. Also, a couple of benchmark problems are used to evaluate performance. The integrated scheduling method in this research can be effectively epplied to the real case.

• 한국시뮬레이션학회논문지
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• 제19권3호
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• pp.45-54
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• 2010

반도체 제조공정에 내재된 복잡성은 작업일정(job scheduling) 문제를 해석적 방법으로는 풀기 어렵기 때문에 보통 시스템 파라미터의 변화에 대한 효과를 이산사건 모델링 시뮬레이션에 의존하여 왔다. 한편 장비 고장 등 예측 불가능한 사건들은 고정된 작업일정 기법을 사용할 경우 전체 공정의 효율을 악화시킨다. 따라서 이러한 불확실성에 대해 최적의 성능을 내기 위해서는 작업일정을 실시간으로 대처 변경하는 것이 필요하다. 본 논문은 반도체 제조 공정에 대해 시스템 제어관점의 접근방법을 적용하여 이 문제에 적응형 실시간 작업제어 틀을 제안하고, DEVS 모델링 시뮬레이션 환경을 기반으로 제안된 틀을 설계 구현하였다. 제안된 방법은 기존의 임기응변적인 소프트웨어적인 방법에 비추어볼 때 전체 시스템을 이해하기 쉬우면서도 또한 추가되는 작업제어 규칙도 쉽게 추가 적용할 수 있는 유연성을 장점으로 가지고 있다. 여러 가지 실험결과 제안된 적응형 실시간 작업제어 프레임워크는 고정 작업규칙 방법에 비해 훨씬 나은 결과를 보여주어 그 효용성을 입증하였다.

• 대한안전경영과학회:학술대회논문집
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• 대한안전경영과학회 2004년도 춘계학술대회
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• pp.49-49
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• 2004

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권3호
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• pp.1071-1090
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• 2016

Most of scheduling methods in the Grid only consider one special attribute of the resource or one aspect of QoS (Quality of Service) of the job. In this paper, we focus on the problem that how to consider two aspects simultaneously. Based on the requirements of the jobs and the attributes of the resources, jobs are categorized into three kinds: CPU-overload, memory-overload, and bandwidth-overload jobs. One job may belong to different kinds according to different attributes. We schedule the jobs in different categories in different orders, and then propose a scheduling method-MTS (multiple attributes scheduling method) to schedule Grid resources. Based on the comparisons between our method, Min-min, ASJS (Adaptive Scoring Job Scheduling), and MRS (Multi-dimensional Scheduling) show: (1) MTS reduces the execution time more than 15% to other methods, (2) MTS improves the number of the finished jobs before the deadlines of the jobs, and (3) MTS enhances the file size of transmitted files (input files and output files) and improves the number of the instructions of the finished jobs.

• 산업기술연구
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• 제28권A호
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• pp.51-61
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• 2008

In these days, domestic manufacturers are faced with managerial difficulties such as the increasing competition in their industry and the increasing power of customers. In this situation, they have to satisfy their customers with high quality of their products and meeting due date of their orders. Production of the order within due date is an important factor for improving enterprise competitiveness. The causes of occurrence of tardiness may be wrong product scheduling, unexpected events in field and so on, a way to minimize tardiness is use of alternative machines, overwork, outsourcing and etc.. In this study, we deal with a scheduling problem that can minimize tardiness using alternative machines. This paper provides a mathematical program and a heuristic method for job shop scheduling for minimizing tardiness with alternative machines. And a proposed heuristic method is verified comparing with optimal solution obtained by ILOG CPLEX.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권1호
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• pp.237-252
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• 2017

In recent years, data centers have become the core infrastructure to deal with big data processing. For these big data applications, network transmission has become one of the most important factors affecting the performance. In order to improve network utilization and reduce job completion time, in this paper, by real-time monitoring from the application layer, we propose job-aware priority scheduling. Our approach takes the correlations of flows in the same job into account, and flows in the same job are assigned the same priority. Therefore, we expect that flows in the same job finish their transmissions at about the same time, avoiding lagging flows. To achieve load balancing, two approaches (Flow-based and Spray) using ECMP (Equal-Cost multi-path routing) are presented. We implemented our scheme using NS-2 simulator. In our evaluations, we emulate real network environment by setting background traffic, scheduling delay and link failures. The experimental results show that our approach can enhance the Hadoop job execution efficiency of the shuffle stage, significantly reduce the network transmission time of the highest priority job.