• Industrial Engineering and Management Systems
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• 제10권3호
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• pp.203-208
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• 2011

Job shop scheduling is well-known as one of the hardest combinatorial optimization problems and has been demonstrated to be NP-hard problem. In the past decades, several researchers have devoted their effort to develop evolutionary algorithms such as Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) for job shop scheduling problem. Differential Evolution (DE) algorithm is a more recent evolutionary algorithm which has been widely applied and shown its strength in many application areas. However, the applications of DE on scheduling problems are still limited. This paper proposes a one-stage differential evolution algorithm (1ST-DE) for job shop scheduling problem. The proposed algorithm employs random key representation and permutation of m-job repetition to generate active schedules. The performance of proposed method is evaluated on a set of benchmark problems and compared with results from an existing PSO algorithm. The numerical results demonstrated that the proposed algorithm is able to provide good solutions especially for the large size problems with relatively fast computing time.

• Journal of information and communication convergence engineering
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• 제11권4호
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• pp.235-240
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• 2013

Cloud systems are popular computing environment because they can provide easy access to computing resources for users as well as efficient use of resources for companies. The resources of cloud computing are heterogeneous and jobs have various characteristics. One such issue is effective job scheduling. Scheduling in the cloud system may be defined as a multiple criteria decision model. To address this issue, this paper proposes a priority-based two-step job scheduling algorithm. On the first level, jobs are classified based on preference. Resources are dedicated to a job if a deadline failure would cause severe results or critical business losses. In case of only minor discomfort or slight functional impairment, the job is scheduled using a best effort approach. On the second level, jobs are allocated to adequate resources through their priorities that are calculated by the analytic hierarchic process model. We then analyze the proposed algorithm and make a scheduling example to confirm its efficiency.

• 산업경영시스템학회지
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• 제25권3호
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• pp.41-49
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• 2002

In the study, for the practical approaches of job shop scheduling, we propose the new dispatching rules of job shop scheduling in order to complement the practical applications in the existing researches. The assumed situation for the practical approaches considers the following; relaxation of assumption for capacity constraint by machine flexibility, the addition of the common use of jig and fixture, unbalanced machine workloads and duedate tightness, and produces fast rescheduling that reflects unexpected situations. The performance of the new dispatching rules is compared and analyzed with the existing methods through the computer experiments in the assumed conditions. The results can be useful to improving a field application of the job shop scheduling.

• 한국산업경영시스템학회:학술대회논문집
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• 한국산업경영시스템학회 2002년도 춘계학술대회
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• pp.91-98
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• 2002

In the study, we propose, for the practical approaches of job shop scheduling, the new dispatching rules of Job shop scheduling in order to complement the practical applications in the existing researches. The performance of the new dispatching rules is compared and analyzed with the existing methods through the computer experiments in the assumed conditions. The results can be useful to improving a field application of the job shop scheduling.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 2003년도 추계학술대회 및 정기총회
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• pp.85-88
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• 2003

In case that any jobs in a Job Shop can be scheduled on more than one machine and may have flexible operation sequences, with considering such case it is very difficult and complex to make the optimal process plans and scheduling. But they should be considered for an integrated model to perform more effective process planning and scheduling in this job shop problem. In this paper, we propose GA-based scheduling method to integrate effectively the problem of alternative machines, alternative operation sequences and scheduling. The performance of proposed GA is evaluated through comparing integrated scheduling with not integrated scheduling in molding company with alternative machines and operation sequences. Also, we use benchmark problems to evaluate performance. The scheduling method in this research will apply usefully to real world scheduling problems.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국내학술편); Seoul National University, Seoul; 20-22 Oct. 1993
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• pp.1095-1098
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• 1993

This paper presents linear programming neural networks for job-shop scheduling. The starting times of tasks and constraints are formulated as the linear programming problem. A modified Hopfield neural network is proposed for solving job-shop scheduling.

• 한국정보과학회논문지:시스템및이론
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• 제34권7호
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• pp.304-318
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• 2007

그리드(Grid) 컴퓨팅은 지리적으로 분산된 컴퓨팅 자원들을 네트워크로 연동시켜 서로 공유 될 수 있도록 해주는 서비스이다. 본 논문에서는 그리드 컴퓨팅 시스템을 구성하는 전체 노드를 대상으로 작업을 분배하는 메타 스케줄링 정책과 특정 한 개의 노드 내에서 작업을 분배하는 작업 스케줄링을 동시에 고려하는 하이브리드 스케줄링 기법을 제안한다. 그리드 컴퓨팅 노드로 제출된 작업을 필요 프로세서 수와 예상 작업수행 시간에 따라 구분하여 우선순위가 높은 작업은 작업 큐(Job Queue)로, 우선순위가 낮은 작업과 원거리 작업은 백필 큐(Backfill Queue)로 할당시킴으로써, 그리드 컴퓨팅 시스템의 성능을 높이는 방법을 연구한다. 다양한 실험을 통하여 제안된 기법들의 성능을 평가하며, 그리드 컴퓨팅 시스템의 이용률이 높아지고, 작업 지연시간이 감소됨을 확인한다.

• 한국통신학회논문지
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• 제5권1호
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• pp.83-87
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• 1980

階層構造 COMPUTER Network을 通한 工程制御로 Processing을 分數하여 Fault tolerance를 極大化시키며 複雜하고 多樣한 變數의 相互關係를 週期的으로 監視制御하는 分散制御 Processor JOB은 그 週期와 實行時間으로 定義할 수 있다. 모든 JOB에 대하여 Tree structure인 關係를 가진 subset들로 구성하여 이에 JOB Scheduling Algorithm을 求하여 본 결과 FCFS(Fist Come/First Service)인 Schedule 보다 Processor의 利用에 있어 Loose Time을 減少시키고 處理 可能時間 確保에 有利하였다.

• 산업융합연구
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• 제1권2호
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• pp.69-79
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• 2003

In order to solve scheduling, many techniques including optimization and heuristics methods have been proposed. However, these conventional approaches are usually inadequate to obtain a satisfactory solution because of a NP-Complete which requires extensive computation effort. The aim of this paper is to develop an expert system for job shop scheduling using an AI technique. Through this system, the user can choose one of several performances. If one performance is chosen, then the system solves a scheduling in order to satisfy that performance. Then, this system decides urgent job. This system can utilize production resources efficiently and minimize work-in-process inventories and tardy jobs.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 2002년도 춘계공동학술대회
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• pp.944-948
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• 2002

In industrial production setting scheduling problems of detalied day-to-day operations are often ordeals to production practitioners. For those who have scheduling experience with the Gantt Chart, the job oriented heuristic scheduling has illustrated its merits in solving practically large stale scheduling problems. It schedules all operations of a job within a finite capacity before considering the next job. This paper introduces a new LSB (load smoothing backward) scheduling algorithm for the job oriented heuristic scheduling. Through the computer simulation in a hypothetical setting, this paper provides a comparison of LSB scheduling with existing algorithms and a guideline for selecting the suitable algorithm for certain industrial setting.