• 산업경영시스템학회지
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• 제23권56호
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• pp.9-18
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• 2000

This paper considers the problem of two-machine, M-parallel flow shop scheduling to minimize makespan, and proposes a series of heuristic algorithms and a branch and bound algorithm. Two processing times of each job at two machines on each line are identical on any line. Since each flow-shop line consists of two machines, Johnson's sequence is optimal for each flow-shop line. Heuristic algorithms are developed in this paper by combining a "list scheduling" method and a "local search with global evaluation" method. Numerical experiments show that the proposed heuristics can efficiently give optimal or near-optimal schedules with high accuracy. with high accuracy.

• 산업경영시스템학회지
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• 제14권23호
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• pp.47-55
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• 1991

In automated assembly line, an automatic guided vehicle system(AGVS) represents a mire versatile means of moving materials automatically. In this paper, the vehicles not only provide the transportation medium between workstations but also as mobile workstations. The objective for the developed model is the determination of the appropriate time to control AGV based assembly line in order to minimize production makespan while maximizing the efficient use of vehicles. In this paper, we consider the finished goods of two types which are produced in assembly line. The assembly line is considered with and without queue. Because no buffer are present in case 1. this model seeks to determine the point in time at which vehicles should be launched in the assembly line without experiencing a delay. The case 2 model also seek to determine the vehicle launch times while minimizing production makespan. The assumption in this model is that the maximum queue size cannot exceed 1 at any time.

• 산업융합연구
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• 제3권1호
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• pp.19-31
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• 2005

This paper deals with the sequencing problem in the operation of the manufacturing systems with the constraint of buffer capacity. Some of studies for this theme have been progressed for several years. And then most of them considered only one objective, such as maximum lateness, machine utilization, makespan, mean flowtime and so on. This study deal with two objectives of the delivery for customers and the idle time of machines for producers. For the decision of sequence, the utility function is used. The developed heuristic algorithm presents a good solution. Through a numerical example, the procedures of the job sequencing is explained.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 2000년도 추계학술대회 및 정기총회
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• pp.148-148
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• 2000

• 인터넷정보학회논문지
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• 제6권6호
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• pp.99-106
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• 2005

멀티프로세서 시스템에서 스케줄링은 매우 중요한 부분이지만, 최적의 해를 구하는 것이 복잡하여 다양한 휴리스틱 방법들에 의한 스케줄링 알고리즘들이 제안되고 있다. 최근 유전 알고리즘을 사용한 멀티프로세서 스케줄링 알고리즘들이 제시되고 있지만, 제시된 알고리즘 대부분은 한가지만의 목적을 가지는 단순한 알고리즘이다. 본 논문에서는 유전 알고리즘을 이용한 새로운 스케줄링 알고리즘을 제시한다. 또한, 해를 구하는 과정에서 시뮬레이티드 어닐링 (simulated annealing)의 확률을 이용하여 유전 알고리즘의 성능을 개선시킨다. 제시된 알고리즘은 태스크들의 최종 수행 완료 시간 (makespan)을 최소화하는 것과 사용된 프로세서의 수를 최소화하는 두 가지의 목표를 가진다. 모의 실험을 통하여 제시된 알고리즘이 다른 알고리즘보다 최종 수행 완료 시간과 사용된 프로세서의 수에서 더 나은 결과를 보임을 확인할 수 있었다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권8호
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• pp.2821-2839
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• 2015

Energy consumption by large computing systems has become an important research theme not only because the sources of energy are depleting fast but also due to the environmental concern. Computational grid is a huge distributed computing platform for the applications that require high end computing resources and consume enormous energy to facilitate execution of jobs. The organizations which are offering services for high end computation, are more cautious about energy consumption and taking utmost steps for saving energy. Therefore, this paper proposes a scheduling technique for Minimizing Energy consumption using Adapted Genetic Algorithm (MiE-AGA) for dependent tasks in Computational Grid (CG). In MiE-AGA, fitness function formulation for energy consumption has been mathematically formulated. An adapted genetic algorithm has been developed for minimizing energy consumption with appropriate modifications in each components of original genetic algorithm such as representation of chromosome, crossover, mutation and inversion operations. Pseudo code for MiE-AGA and its components has been developed with appropriate examples. MiE-AGA is simulated using Java based programs integrated with GridSim. Analysis of simulation results in terms of energy consumption, makespan and average utilization of resources clearly reveals that MiE-AGA effectively optimizes energy, makespan and average utilization of resources in CG. Comparative analysis of the optimization performance between MiE-AGA and the state-of-the-arts algorithms: EAMM, HEFT, Min-Min and Max-Min shows the effectiveness of the model.

• Korean Chemical Engineering Research
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• 제43권5호
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• pp.571-578
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• 2005

불연속 화학공정은 소비자 수요에 탄력성 있게 대처할 수 있는 장점이 있는 반면에 그 특유의 동특성 때문에 복잡하고, 계획된 조업 시간과 실제 조업 시간 사이에서 외란(disruption) 또는 불확실 변수(uncertainty)에 의한 차이가 자주 발생하는 단점이 있다. 이에, 본 논문에서는 예측 생산계획(predictive scheduling)에 의해 결정된 생산계획에서 미래에 발생하는 공정 변수 값의 변화를 실시간으로 예측 생산계획을 수정, 제시하여 주는 생산 계획 시스템인 동적 생산계획(reactive scheduling) 기법을 개발하였다. 불확실 인자를 고려한 동적 생산계획에서, 본 논문에서는 장치 이상(equipment failure)이 발생하였을 때 공정 운전조건의 변화를 실시간으로 반영하여, 예측 생산계획(predictive scheduling) 모델에 의하여 제시된 전체 생산 계획을 최대한 유지하고 공정 변수의 변화를 실시간으로 반영하기 위하여 right shift rescheduling과 total regeneration 기법을 사용하였다. 또한, 불확실 인자의 발생 전후의 predictive scheduling과 reactive scheduling 간의 변화 정도를 측정하는 수단인 schedule stability 위하여, 본 논문에서는 수정된 sequence deviation과 percentage change in makespan을 사용하여 제안된 동적 생산계획의 안정성을 측정하였다. 본 논문에서 제안한 동적 생산계획 시스템은 기존에 제시되었던 경험 법칙에 의한 결과값에 비해 좋은 결과를 보여주었다.

• 산업공학
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• 제24권4호
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• pp.281-294
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• 2011

This paper considers the rail crane scheduling problem which is defined as determining the sequence of loading/unloading container on/from a freight train. The objective is to minimize the weighted sum of the range of order completion time and makespan. The range of order completion time implies the difference between the maximum of completion time and minimum of start time of each customer order consisting of jobs. Makespan refers to the time when all the jobs are completed. In a rail freight terminal, logistics firms as a customer wish to reduce the range of their order completion time. To develop a methodology for the crane scheduling, we formulate the problem as a mixed integer program and develop three metaheuristics, namely, genetic algorithm, simulated annealing, and tabu search. To validate the effectiveness of heuristic algorithms, computational experiments are done based on a set of real life data. Results of the experiments show that heuristic algorithms give good solutions for small-size and large-size problems in terms of solution quality and computation time.

• Industrial Engineering and Management Systems
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• 제8권3호
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• pp.171-180
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• 2009

Population learning algorithm (PLA) is a population-based method that was inspired by the similarities to the phenomenon of social education process in which a diminishing number of individuals enter an increasing number of learning stages. The study aims to develop a framework that repeatedly applying the PLA to solve the discrete resource constrained project scheduling problem with two objectives: minimizing project makespan and renewable resource availability, which are two most common concerns of management when a project is being executed. The PLA looping framework will provide a number of near Pareto optimal schedules for the management to make a choice. Different improvement schemes and learning procedures are applied at different stages of the process. The process gradually becomes more and more sophisticated and time consuming as there are less and less individuals to be taught. An experiment with ProGen generated instances was conducted, and the results demonstrated that the looping framework using PLA outperforms those using genetic local search, particle swarm optimization with local search, scatter search, as well as biased sampling multi-pass algorithm, in terms of several performance measures of proximity. However, the diversity using spread metric does not reveal any significant difference between these five looping algorithms.

• 대한기계학회논문집A
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• 제24권8호
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• pp.2131-2142
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• 2000

As recent production facilities are usually operated with unmanned material-handling system, the development of an efficient schedule with deadlock avoidance becomes a critical problem. Related researches on deadlock avoidance usually focus on real-time control of manufacturing system using deadlock avoidance policy. But little off-line optimization of deadlock-free schedule has been reported. This paper presents an optimization method for deadlock-free scheduling for Job-Shop system with no buffer. The deadlock-free schedule is acquired by the procedure that generates candidate lists of waiting operations, and applies a deadlock avoidance policy. To verify the proposed approach, simulation resultsare presented for minimizing makespan in three problem types. According to the simulation results the effect of each deadlock avoidance policy is dependent on the type of problem. When the proposed LOEM (Last Operation Exclusion Method) is employed, computing time for optimization as well as makespan is reduced.