• Journal of Korean Institute of Industrial Engineers
• /
• v.12 no.1
• /
• pp.19-30
• /
• 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.

• IE interfaces
• /
• v.12 no.3
• /
• pp.354-361
• /
• 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
• /
• v.10 no.1
• /
• pp.7-14
• /
• 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.

• Journal of Korean Institute of Industrial Engineers
• /
• v.40 no.3
• /
• pp.305-312
• /
• 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.

• Journal of Korean Institute of Industrial Engineers
• /
• v.22 no.3
• /
• pp.517-532
• /
• 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.

• Journal of Korean Institute of Industrial Engineers
• /
• v.18 no.2
• /
• pp.141-147
• /
• 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
• /
• 1989.10a
• /
• pp.819-824
• /
• 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.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 1996.04a
• /
• pp.83-86
• /
• 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.

• The Transactions of the Korea Information Processing Society
• /
• v.6 no.4
• /
• pp.959-968
• /
• 1999

several papers have reported that parallel heuristics or hybrid approaches combining several heuristics can get better results. However, the parallelization and hybridization of any search methods on the single CPU type computer need enormous computation time. that case, we need more elegant combination method. For this purpose, we propose Fast Model of Parallel Heuristics(FMPH). FMPH is based on the island model of parallel genetic algorithms and takes local search to the elite solution obtained form each island(sub group). In this paper we introduce how can we adapt FMPH to the job-shop scheduling problem notorious as the most difficult NP-hard problem and report the excellent results of several famous benchmark problems.

• Journal of the Korean Society of Earth Science Education
• /
• v.15 no.2
• /
• pp.142-157
• /
• 2022

Heuristic is a empirical method that is used quickly when uncertainty or insufficient time and information are insufficient. The purpose of this study is to find out what heuristics appear in the processing of the experimental manual among science experiment activities of elementary school students. To do this, 20 fifth-grade elementary school students (female 10 and male 10) were required to conduct scientific experimental activities as research participants to collect experimental behavior data and gaze movement data, and retrospective interviews were conducted. The collected data extracted and conceptualized behavior by heuristics. As a result of the study, there were five heuristics that appeared in the processing of the experimental manual: "reducing the difference between the target state and the current state," "guessing the experimental procedure," "paying attention to the expected results," "comparing with the picture of the experimental manual," and "using a trial and error strategy." According to each concept of heuristics, there were favorable and unfavorable aspects for experimental activities. In science experiment activities that students experience for the first time, there is a lack of information and the situation is uncertain, so behavior by heuristics appears in nature. Therefore, educators need to understand students' heuristics and guide scientific experimental activities.