• 한국정보과학회논문지:시스템및이론
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• 제31권1_2호
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• pp.95-101
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• 2004

이질적인 계산자원들로 구성된 분산 컴퓨팅 환경에서 의존성이 존재하지 않는 독립적인 작업들을 자원들에 배치하기 위한 방법은 NP-Complete 문제로 알려져 있다［1］. 이질적인 자원으로 구성된 시스템의 대표적인 예가 GRID［2］이다. 현재까지 그리드 시스템에서 스케줄링 문제를 풀기 위한 다양한 휴리스틱 스케줄링 방법이 연구되어 왔다［1,3,4,5］. 스케줄링 방법은 정적인 방법과 동적인 방법으로 나뉘어진다. 동적 스케줄링 방법은 작업의 선후 관계를 예측할 수 없는 상황에서 사용되며 동적 스케줄링 방법은 스케줄링 시기에 따라 온라인방식과 배치방식으로 나뉘어진다［1,6］. 본 논문에서는 새로운 온라인 휴리스틱 스케줄링 알고리즘을 제안하였으며 제안된 스케줄링 알고리즘의 성능이 기존의 스케줄링 알고리즘의 성능보다 뛰어남을 시뮬레이션을 통하여 보였다.

• 경영과학
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• 제20권1호
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• pp.51-64
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• 2003

The JSSP (Job Shop Scheduling Problem) Is one of the most general and difficult of all traditional scheduling problems. The goal of this research is to develop an efficient scheduling method based on genetic algorithm to address JSSP. we design scheduling method based on SGA (Single Genetic Algorithm) and PGA (Parallel Genetic Algorithm). In the scheduling method, the representation, which encodes the job number, is made to be always feasible, initial population is generated through integrating representation and G&T algorithm, the new genetic operators and selection method are designed to better transmit the temporal relationships in the chromosome, and island model PGA are proposed. The scheduling method based on genetic algorithm are tested on five standard benchmark JSSPs. The results were compared with other proposed approaches. Compared to traditional genetic algorithm, the proposed approach yields significant improvement at a solution. The superior results indicate the successful Incorporation of generating method of initial population into the genetic operators.

• 제어로봇시스템학회논문지
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• 제10권1호
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• pp.87-95
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• 2004

We proposed the division algorithm that was aimed at dividing system models. It used a transitive matrix to express the relation between place and transition. And the division algorithm was applied to the scheduling problem, with the division-scheduling algorithm. The division-scheduling algorithm was able to calculate the divided subnet table. And it is able to reduce the analysis complexity. In this study, we applied the proposed division algorithm and division-scheduling algorithm to flexible manufacturing system models. We compared the efficiency and performance of the division-scheduling algorithm with the Hillion algorithm, Korbaa algorithm, and Unfolding algorithm proposed in previous researches.

• 한국컴퓨터정보학회논문지
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• 제6권1호
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• pp.67-73
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• 2001

본 논문에서는 광대역 가입자 엑세스망의 인프라 기술인 ATM 노드에서의 셀 스케줄링 알고리즘을 제안한다. 기존의 트레인 스케줄링 알고리즘(Train scheduling algorithm)이나 챠오 스케쥬링 알고리즘(Chao scheduling algorithm), 동적 스케줄링 알고리즘(Dynamic scheduling algorithm) 등의 ATM 스케줄링 알고리즘들은 셀 손실률이 높고 전송 채널의 낭비가 많은 단점이 있다. 본 연구에서는 다양한 멀티미디어 서비스 제공을 위해 입력 소스 트래픽의 QoS 등급에 기초를 둔 제어 방식을 제안한다. 먼저 다양한 서비스 품질을 만족시키기 위한 스케줄링 알고리즘과 기능적 구조를 설계하고. 모의실험을 통해 패킷 손실율과 평균지연 측면에서 알고리즘의 성능을 고찰한다.

• 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.

• 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.

• 산업공학
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• 제19권2호
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• pp.153-159
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• 2006

The research of scheduling algorithms for operating the facility of exhibition and convention can be hardly found in published papers. This study is to find problems in the process of operating the facility of exhibition and convention and to develop the scheduling algorithm satisfying those problems. The scheduling algorithm of this paper is developed through constructing the mathematical model and analyzing the mathematical structure of variables and constraints in that model. The scheduling algorithm developed in this paper consists of the first stage of scheduling, the second stage of feasibility routine and the third stage of improving scheduling results. Some experimental results are given to verify the effectiveness of the scheduling algorithm developed in this paper.

• 한국경영과학회지
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• 제27권2호
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• pp.97-109
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• 2002

Manufacturing environments in the real world are subject to many sources of change and uncertainty, such as new job releases, job cancellations, a chance in the processing time or start time of some operation. Thus, the realistic scheduling method should Properly reflect these dynamic environment. Based on the release times of jobs, JSSP (Job Shoe Scheduling Problem) can be classified as static and dynamic scheduling problem. In this research, we mainly consider the dynamic JSSP with continually arriving jobs. The goal of this research is to develop an efficient scheduling method based on GA (Genetic Algorithm) to address dynamic JSSP. we designed scheduling method based on SGA (Sing1e Genetic Algorithm) and PGA (Parallel Genetic Algorithm) The scheduling method based on GA is extended to address dynamic JSSP. Then, This algorithms are tested for scheduling and rescheduling in dynamic JSSP. The results is compared with dispatching rule. In comparison to dispatching rule, the GA approach produces better scheduling performance.

• 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.

• 경영과학
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• 제9권1호
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• pp.119-137
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• 1992

A two phase heuristic algorithm has been developed for the resolution of resource conflicts in a single project scheduling problem. Phase 1 of the algorithm generates a feasible schedule by repairing resource conflicts. Phase 2 finds local improvements in the schedule found in phase 1. Then, the algorithm has been applied to multi project and job shop scheduling. Computational results are compared with those of dispatching procedures. Index Terms-disjunctive constraints, heuristic algorithm, project scheduling, job-shop scheduling.