• 제목/요약/키워드: Hybrid Scheduling Algorithm

검색결과 72건 처리시간 0.023초

Job Shop 일정계획을 위한 혼합 유전 알고리즘 (A Hybrid Genetic Algorithm for Job Shop Scheduling)

  • 박병주;김현수
    • 한국경영과학회지
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    • 제26권2호
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    • pp.59-68
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    • 2001
  • The job shop scheduling problem is not only NP-hard, but is one of the well known hardest combinatorial optimization problems. The goal of this research is to develop an efficient scheduling method based on hybrid genetic algorithm to address job shop scheduling problem. In this scheduling method, generating method of initial population, new genetic operator, selection method are developed. The scheduling method based on genetic algorithm are tested on standard benchmark job shop scheduling problem. The results were compared with another genetic algorithm0-based scheduling method. Compared to traditional genetic, algorithm, the proposed approach yields significant improvement at a solution.

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실시간 시스템에서 성능 향상 기법 (Enhanced Technique for Performance in Real Time Systems)

  • 김명준
    • 한국IT서비스학회지
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    • 제16권3호
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    • pp.103-111
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    • 2017
  • The real time scheduling is a key research area in high performance computing and has been a source of challenging problems. A periodic task is an infinite sequence of task instance where each job of a task comes in a regular period. The RMS (Rate Monotonic Scheduling) algorithm has the advantage of a strong theoretical foundation and holds out the promise of reducing the need for exhaustive testing of the scheduling. Many real-time systems built in the past based their scheduling on the Cyclic Executive Model because it produces predictable schedules which facilitate exhaustive testing. In this work we propose hybrid scheduling method which combines features of both of these scheduling algorithms. The original rate monotonic scheduling algorithm didn't consider the uniform sampling tasks in the real time systems. We have enumerated some issues when the RMS is applied to our hybrid scheduling method. We found the scheduling bound for the hard real-time systems which include the uniform sampling tasks. The suggested hybrid scheduling algorithm turns out to have some advantages from the point of view of the real time system designer, and is particularly useful in the context of large critical systems. Our algorithm can be useful for real time system designer who must guarantee the hard real time tasks.

지역별 예비력 제약과 융통전력을 고려한 발전기 예방정비 계획 해법 (Generating Unit Maintenance Scheduling Considering Regional Reserve Constraints and Transfer Capability Using Hybrid PSO Algorithm)

  • 박영수;박준호;김진호
    • 전기학회논문지
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    • 제56권11호
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    • pp.1892-1902
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    • 2007
  • This paper presents a new generating unit maintenance scheduling algorithm considering regional reserve margin and transfer capability. Existing researches focused on reliability of the overall power systems have some problems that adequate reliability criteria cannot be guaranteed in supply shortage regions. Therefore specific constraints which can treat regional reserve ratio have to be added to conventional approaches. The objective function considered in this paper is the variance (second-order momentum) of operating reserve margin to levelize reliability during a planning horizon. This paper focuses on significances of considering regional reliability criteria and an advanced hybrid optimization method based on PSO algorithm. The proposed method has been applied to IEEE reliability test system(1996) with 32-generators and a real-world large scale power system with 291 generators. The results are compared with those of the classical central maintenance scheduling approaches and conventional PSO algorithm to verify the effectiveness of the algorithm proposed in this paper.

Hybrid Scheduling Algorithm based on DWDRR using Hysteresis for QoS of Combat Management System Resource Control

  • Lee, Gi-Yeop
    • 한국컴퓨터정보학회논문지
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    • 제25권1호
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    • pp.21-27
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    • 2020
  • 본 논문에서는 전투관리체계의 QoS를 향상시키기 위해 동적 가중 결손 라운드로빈과 우선 순위 기반의 혼합 스케줄링 알고리즘을 제안한다. 제안된 알고리즘인 DWDRR은 큐의 트래픽과 중요도에 따라 가중치를 동적으로 부여하여 패킷을 전송하는 방법이다. 제안된 알고리즘의 타당성을 분석하기 위해 모의실험을 통해 제안된 알고리즘이 특정구간에서 높은 효율성을 나타내는 것을 증명하였다. 따라서 기존의 알고리즘과 제안된 알고리즘을 혼합하여 사용하는 방법을 제안한다. 또한, 빈번한 기법 전환을 방지하기 위해 히스테리시스 기법을 적용하였다. 제안한 알고리즘은 동일한 트래픽에서 기존 알고리즘보다 낮은 패킷 손실률과 지연 시간을 나타낸다.

Optimal Time Slot Assignment Algorithm for Combined Unicast and Multicast Packets

  • Lee, Heyung-Sub;Joo, Un-Gi;Lee, Hyeong-Ho;Kim, Whan-Woo
    • ETRI Journal
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    • 제24권2호
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    • pp.172-175
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    • 2002
  • This paper considers a packet-scheduling algorithm for a given combined traffic of unicast and multicast data packets and proposes a hybrid router with several dedicated buses for multicast traffic. Our objective is to develop a scheduling algorithm that minimizes schedule length for the given traffic in the hybrid router. We derive a lower bound and develop an optimal solution algorithm for the hybrid router.

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작업준비시간이 없는 이종 병렬설비에서 총 소요 시간 최소화를 위한 미미틱 알고리즘 기반 일정계획에 관한 연구 (A Study on Memetic Algorithm-Based Scheduling for Minimizing Makespan in Unrelated Parallel Machines without Setup Time)

  • 이태희;유우식
    • 대한안전경영과학회지
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    • 제25권2호
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    • pp.1-8
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    • 2023
  • This paper is proposing a novel machine scheduling model for the unrelated parallel machine scheduling problem without setup times to minimize the total completion time, also known as "makespan". This problem is a NP-complete problem, and to date, most approaches for real-life situations are based on the operator's experience or simple heuristics. The new model based on the Memetic Algorithm, which was proposed by P. Moscato in 1989, is a hybrid algorithm that includes genetic algorithm and local search optimization. The new model is tested on randomly generated datasets, and is compared to optimal solution, and four scheduling models; three rule-based heuristic algorithms, and a genetic algorithm based scheduling model from literature; the test results show that the new model performed better than scheduling models from literature.

그룹 테크놀로지 경제적 로트 일정계획문제를 위한 복합 유전자 알고리즘 (Solving Group Technology Economic Lot Scheduling Problem using a Hybrid Genetic Algorithm)

  • 문일경;차병철;배희철
    • 한국경영과학회:학술대회논문집
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    • 한국경영과학회/대한산업공학회 2005년도 춘계공동학술대회 발표논문
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    • pp.947-951
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    • 2005
  • The concept of group technology has been successfully applied to many production systems including flexible manufacturing systems. In this paper we apply group technology principles to the economic lot scheduling problem which has been intensively studied over 40 years. We obtain a production schedule of several family products on a single facility where setup times and costs can be reduced by using the concept of group technology. We develop a heuristic algorithm and a hybrid genetic algorithm for the group technology economic lot scheduling problem (GT-ELSP). Numerical example shows that the developed heuristic and the hybrid genetic algorithm outperform the existing heuristics.

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FMS환경에서 다단계 일정계획문제를 위한 적응형혼합유전 알고리즘 접근법 (Adaptive Hybrid Genetic Algorithm Approach to Multistage-based Scheduling Problem in FMS Environment)

  • 윤영수;김관우
    • 지능정보연구
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    • 제13권3호
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    • pp.63-82
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    • 2007
  • 본 논문에서는 유연제조시스템(FMS)에서 다단계스케줄링 문제를 효율적으로 해결하기 위한 적응형 혼합유전 알고리즘(ahGA) 접근법을 제안한다. 제안된 ahGA는 FMS의 해를 개선시키기 위하여 이웃탐색기법을 사용하며, 유전탐색과정에서의 수행도를 향상시키기 위해 유전알고리즘(GA)의 파라메터들을 조정하기 위한 적응형 구조를 사용한다. 수치실험에서는 제안된 ahGA와 기존의 알고리즘들 간의 수행도를 비교하기 위하여 두가지형태의 다단계스케줄링문제를 제시한다. 실험결과는 제안된 ahGA가 기존의 알고리즘들 보나 더 뛰어난 수행도를 보여주고 있다.

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2단계 혼합흐름공정에서 납기 지연 작업수의 최소화를 위한 분지한계 알고리듬 (A Branch and Bound Algorithm for Two-Stage Hybrid Flow Shop Scheduling : Minimizing the Number of Tardy Jobs)

  • 최현선;이동호
    • 대한산업공학회지
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    • 제33권2호
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    • pp.213-220
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    • 2007
  • This paper considers a two-stage hybrid flow shop scheduling problem for the objective of minimizing the number of tardy jobs. Each job is processed through the two production stages in stages, each of which has multiple identical parallel machines. The problem is to determine the allocation and sequence of jobs at each stage. A branch and bound algorithm that gives the optimal solutions is suggested that incorporates the methods to obtain the lower and upper bounds. Dominance properties are also suggested to reduce the search space. To show the performance of the algorithm, computational experiments are done on randomly generated problems, and the results are reported.