• 대한산업공학회지
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• 제12권1호
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• pp.19-30
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• 1986

This paper provides an evaluation of static flowshop scheduling heuristics for minimizing makespan as an objective function in the dynamic flowshop model, in which new jobs with stochastic processing times arrive at the shop randomly over time and are added into the waiting jobs for processing. A total of sixteen scheduling heuristics, including several revisions and combinations of previously reported me-sixteen scheduling heuristics, including several revisions and combinations of previously reported methods, are surmmarized. These scheduling rules are evaluated via computer using a SLAM discrete event simulation model. The results for the simulation are analyzed using both statistical and nonstatistical methods. The results from the study suggest which of the popular scheduling rules hold promise for application to practical dynamic flowshop problems.

• 산업공학
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• 제12권3호
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• pp.354-361
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• 1999

In this paper, resource leveling heuristics are developed for ship erection scheduling. The heuristics, which enable scheduling with limited resources, are composed of the gradual resource limit decrease anti the resource allocation. At first, earliest start(ES) schedule is derived by PERT to get initial resource limit. And then, the heuristics lower the resource limits by a given increment and derive a new schedule from day-by-day resource allocation procedure. The procedure is repeated until the project duration reaches at the given ship erection duration, called dock cycle. Through the application of the heuristics for real world ship erection projects, wc can observe significant improvement in resource leveling.

• Industrial Engineering and Management Systems
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• 제10권1호
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• pp.7-14
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• 2011

In solving the Job Shop Scheduling Problem, the best solution rarely is completely random; it follows one or more rules (heuristics). The Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Simulated Annealing, and Tabu search, which belong to the Evolutionary Computations Algorithms (ECs), are not efficient enough in solving this problem as they neglect all conventional heuristics and hence they need to be hybridized with different heuristics. In this paper a new algorithm titled "Shaking Optimization Algorithm" is proposed that follows the common methodology of the Evolutionary Computations while utilizing different heuristics during the evolution process of the solution. The results show that the proposed algorithm outperforms the GA, PSO, SA, and TS algorithms, while being a good competitor to some other hybridized techniques in solving a selected number of benchmark Job Shop Scheduling problems.

• 대한산업공학회지
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• 제40권3호
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• pp.305-312
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• 2014

This research deals with a problem that minimizes makespan in a non-identical parallel machine system with sequence and machine dependent setup times and machine dependent processing times. We first present a new mixed integer programming formulation for the problem, and using this formulation, one can easily find optimal solutions for small problems. However, since the problem is NP-hard and the size of a real problem is large, we propose four heuristic algorithms including genetic algorithm based heuristics to solve the practical big-size problems in a reasonable computational time. To assess the performance of the algorithms, we conduct a computational experiment, from which we found the heuristic algorithms show different performances as the problem characteristics are changed and the simple heuristics show better performances than genetic algorithm based heuristics for the case when the numbers of jobs and/or machines are large.

• 대한산업공학회지
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• 제22권3호
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• pp.517-532
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• 1996

The area and time-dependent vehicle scheduling problem(ATVSP) is a generalization of the vehicle scheduling problem in which the travel speed between two locations depends on the passing areas and time of day. We propose a simple model for estimating area and time-dependent travel speeds in the ATVSP that relieves much burden for the data collection and storage problems. A mixed integer nonlinear programming formulation of the ATVSP is presented. We also propose three heuristics for the ATVSP, developed by extending and modifying existing heuristics for conventional vehicle scheduling problems. The results of computational experiments demonstrate that the proposed estimation model performs well and the saving method is the best among the three heuristics.

• 대한산업공학회지
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• 제18권2호
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• pp.141-147
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• 1992

This article evaluates the efficiency of three branch-and-bound heuristics for a job scheduling problem that minimizes the sum of absolute deviations of completion times from a common due date. To improve the performance of the branch-and-bound procedure, Algorithm SA is presented for the initial feasible schedule and three heuristics : breadth-first, depth-first and best-first search are investigated depending on the candidate selection procedure. For the three heuristics the CPU time, memory space, and the number of nodes generated are computed and tested with nine small examples (6 ${\leq}$ n ${\leq}$ 4). Medium sized random problems (10 ${\leq}$ n ${\leq}$ 30) are also generated and examined. The computational results are compared and discussed for the three heuristics.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1989년도 한국자동제어학술회의논문집; Seoul, Korea; 27-28 Oct. 1989
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• pp.819-824
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• 1989

This paper proposes a new method for the discovery and design of an optimal heat exchanger network. The method is based upon the concept of pinch, a problem reduction technique and the heuristics developed in this work. It generates subproblems in a logical way and solves the subproblems by the heuristics to synthesize an optimal network structure. It is thought that the heuristics can preserve the minimum utility consumption, the minimum number of heat exchanger units, and the minimum number of stream splittings needed for a given problem. The minimum heat exchanger area for the optimal network can then be obtained by adjusting the temperatures associate with the heat exchanger in the optimal network structure. The method is applied to the problems appeared in the literatures. The results show the reductions in the number of heat exchanger units for some problems.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 1996년도 춘계공동학술대회논문집; 공군사관학교, 청주; 26-27 Apr. 1996
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• pp.83-86
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• 1996

In this paper we study the problem of augmenting a physical network to improve the topology for new survivable network architectures. We are given a graph G=(V,E,F), where V is a set of nodes that represents transmission systems which be interconnected by physical links, and E is a collection of edges that represent the possible pairs of nodes between which a direct transmission link can be placed. F, a subset of E is defined as a set of the existing direct links, and E/F is defined as a set of edges for the possible new connection. The cost of establishing network $N_{H}$=(V,H,F) is defined by the sum of the costs of the individual links contained in new link set H. We call that $N_{H}$=(V,H,F) is feasible if certain connectivity constrints can be satisfied in $N_{H}$=(V,H,F). The computational goal for the suggested model is to find a minimum cost network among the feasible solutions. For a k edge (node) connected component S .subeq. F, we charactrize some optimality conditions with respect to S. By this characterization we can find part of the network that formed by only F-edges. We do not need to augment E/F edges for these components in an optimal solution. Hence we shrink the related component into a node. We study some good primal heuristics by considering construction and exchange ideas. For the construction heuristics, we use some greedy methods and relaxation methods. For the improvement heuristics we generalize known exchange heuristics such as two-optimal cycle, three-optimal cycle, pretzel, quezel and one-optimal heuristics. Some computational experiments show that our heuristic is more efficient than some well known heuristics.stics.

• 한국정보처리학회논문지
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• 제6권4호
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• pp.959-968
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• 1999

기존의 많은 논문에서는 병렬휴리스틱법(Parallel Heuristics) 또는 몇 개의 휴리스틱법을 결합하는 하이브리드 시스템(Hybrid system)이 보다 양질의 탐색 결과를 얻을 수 있음을 보고하고 있다. 그러나 단일 프로세스를 가진 범용 컴퓨터상에서의 병렬화와 하이브리드화는 지나치게 많은 탐색시간을 요구한다. 이러한 경우 탐색의 고속화를 위해서는 탐색법간의 보다 적절한 결합법이 요구된다. 이를 위한 방법론으로서 병렬프리스틱법의 고속화모델(Fast Model of Parallel Heuristics : FMPH)을 제안하고 있다. 유전적 알고리즘(Genetic algorithms)의 섬모델(Island Model)에 의거, 다양한 탐색 공간에서 선택된 우수한 엘리트해에 대해서만 선택적으로 국소탐색(local search)의 능력이 뛰어난 타부 탐색법을 도입한다. 본 논문에서는 NP-hard문제 중에서도 가장 어려운 문제로 평가되는 잡숍 스케쥴링 문제(Job-Shop scheduling Problem)에 대해 적용한 병렬프리스틱법의 고속화 모델을 소개하며 모델의 범용성을 입증하기 위해 유명한 벤치마크 문제에 적용하여 얻은 뛰어난 결과를 보고한다.

• 대한지구과학교육학회지
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• 제15권2호
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• pp.142-157
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• 2022

휴리스틱은 불확실하거나 시간과 정보가 충분하지 않을 때 신속하게 사용하는 경험적 방법이다. 본 연구는 초등학생들의 과학실험활동 중 실험매뉴얼 처리에서 나타나는 휴리스틱이 무엇인지 알아보는 것이 목적이다. 이를 위해 초등학교 5학년 학생 20명(여 10, 남 10)을 연구 참여자로 과학 실험활동을 수행하게 하여 실험행동자료과 시선이동자료를 수집하였고, 회고적 인터뷰를 실시하였다. 수집한 자료에서 휴리스틱에 의한 행동을 추출하고 귀납적으로 개념화 하였다. 연구결과, 실험매뉴얼 처리에서 나타나는 휴리스틱은 "목표상태와 현재상태의 차이 줄이기", "실험 절차를 짐작하기", "기대되는 결과에 주의하기", "실험매뉴얼 사진과 비교하기", "시행착오 전략 사용하기"의 5가지였으며, 각 개념에 따라 실험활동에 유리한 측면과 불리한 측면이 나타났다. 학생들이 처음 경험하게 되는 과학실험활동에서는 정보가 부족하고 상황이 불확실하므로 휴리스틱에 의한 행동이 본성적으로 나타난다. 이에 교육자들은 학생들의 휴리스틱에 대해 이해하고 과학실험활동을 지도할 필요가 있다.