• Journal of the Korea Safety Management & Science
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• v.6 no.2
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• pp.141-154
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• 2004

The objective of this paper is to develop the efficient heuristic method for solving the minimum makespan problem of the job shop scheduling. The proposed heuristic method is based on a constraint satisfaction problem technique and a improved randomizing search algorithm. In this paper, ILOG programming libraries are used to embody the job shop model, and a constraint satisfaction problem technique is developed for this model to generate the initial solution. Then, a improved randomizing search algorithm is employed to overcome the increased search time of constrained satisfaction problem technique on the increased problem size and to find a improved solution. Computational experiments on well known MT and LA problem instances show that this approach yields better results than the other procedures.

• Korean Journal of Computational Design and Engineering
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• v.16 no.3
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• pp.207-215
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• 2011

Due to its large size, a ship is first divided into scores of blocks and then each block is constructed through various shops, such as the assembly shop, the painting shop, and the outfitting shop. However, each block may not be directly moved to the next shop and may be temporarily laid on a block stockyard because the working time in each shop is different. If blocks are laid on the block stockyard without any planning, the rearrangement of the blocks by a transporter are required because the blocks have the different in and out time. In this study, an optimal layout method based on the genetic algorithm was proposed in order to minimize the rearrangement of the blocks in the block stockyard. To evaluate the applicability of the proposed method, it was applied to a simple layout problem of the block stockyard.

• Industrial Engineering and Management Systems
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• v.10 no.3
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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.

• Journal of the Korean Institute of Landscape Architecture
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• v.25 no.4
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• pp.51-60
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• 1998

The purpose of this study was investigating the managers' consciousness on the interior landscape in coffee shop, the actual measurement of the space size and greenary spaces of coffee shop for grasping the actual condition of interior landscape. The coffee shop was made and object of this research was 100 cases in the center of Taegu city. The major results of actual measurement of the ratio greenary and spaces are as follows; 1. The ratio greenary spaces in the indoor plants was account for 2.06% of the coffee shop area. 2. The managers recognized that the spaces area of the interior plantscape were narrow comparison with whole spaces area about the interior landscape. 3. A major arrangement type of the interior landscape was the dispersion type. 4. A major plants used for the interior landscape were foliage plants and also most of managers prefered foliage plant. 5.Generally, managers were high interested in the interior landscape but the experience knowledge and investment in the interior landscape were not sufficient.

• Ocean Systems Engineering
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• v.2 no.4
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• pp.271-287
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• 2012

Due to its large size, a ship is first divided into scores of blocks and then each block is constructed through various shops, such as the assembly shop, the painting shop, and the outfitting shop. However, each block may not be directly moved to the next shop and may be temporarily laid at a block stockyard because the working time in each shop is different from each other. If blocks are laid at the block stockyard without any planning, the rearrangement of the blocks by a transporter is required because the blocks have the different in and out time. In this study, a block layout method based on the genetic algorithm was proposed in order to minimize the rearrangement of the blocks in the block stockyard. To evaluate the applicability of the proposed method, it was applied to simple layout problems of the block stockyard. The result shows that the proposed method can yield a block layout that minimizes the total relocation cost of moving obstacle blocks in the block stockyard.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.25 no.2
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• pp.92-101
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• 2002

The Job Shop Scheduling Problem(JSSP) is concerned with schedule of m different machines and n jobs where each job consists of a chain of operations, each of which needs to be processed during an uninterrupted time period of a given length on a given machine. The purpose of this paper is to develop the efficient heuristic method for solving the minimum makespan problem of the large scale job shop scheduling. The proposed heuristic method is based on a Tabu Search(TS) and on a Constraint Satisfaction Technique(CST). In this paper, ILOG libraries is used to embody the job shop model, and a CST is developed for this model to generate the increased solution. Then, TS is employed to overcome the increased search time of CST on the increased problem size md to refine the next-current solution. Also, this paper presents the new way of finding neighbourhood solution using TS. On applying TS, a new way of finding neighbourhood solution is presented. Computational experiments on well known sets of MT and LA problem instances show that, in several cases, our approach yields better results than the other heuristic procedures discussed In literature.

• Journal of the Korean Society of Fashion and Beauty
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• v.3 no.1 s.4
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• pp.20-28
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• 2005

As the size and the diversity of the beauty industry grow, the need for systematic marketing strategy in beauty shop also increases. This study aims at finding 1)how to segment the market of beauty industry based on lifestyle variable and 2)how to set up the corresponding mix strategy on target market. The case of 'B beauty shop' shows that the validity of lifestyle-based segementation model is verified as the shop has posted a drastic financial outcome during last 5 years. In addition, this study implies that the corelation research between lifestyle variables and marketing mix strategy should be included as an important factor in launching a beauty-related business in segmented market.

• Industrial Engineering and Management Systems
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• v.6 no.2
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• pp.119-124
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• 2007

The most difficult and time-intensive issue in the successful implementation of genetic algorithms is to find good parameter setting, one of the most popular subjects of current research in genetic algorithms. In this study, we present a new efficient experimental design method for parameter optimization in a genetic algorithm for general job shop scheduling problem using the Taguchi method. Four genetic parameters including the population size, the crossover rate, the mutation rate, and the stopping condition are treated as design factors. For the performance characteristic, makespan is adopted. The number of jobs, the number of operations required to be processed in each job, and the number of machines are considered as noise factors in generating various job shop environments. A robust design experiment with inner and outer orthogonal arrays is conducted by computer simulation, and the optimal parameter setting is presented which consists of a combination of the level of each design factor. The validity of the optimal parameter setting is investigated by comparing its SN ratios with those obtained by an experiment with full factorial designs.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.5 no.6
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• pp.41-48
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• 1982

This paper analyzed md developed flow - shop sequencing heuristic method. The essence of the heuristic approach is in the application of selective routine that reduce the size of a problem. The advantages of this approach are consistency. Speed, endurance and the ability to cope with more data and larger systems than is humanly possible, In recent years many heuristic procedures have been suggested for the flow - shop sequencing problem. Although limited comparisons of these procedures have been made, a full scale test and evaluation have not been reported previously. The maximum flow - time criterion is selected as the evaluation criterion is selected as the evaluation criterion of flow - shop's efficiency. The author evaluated these 3 heuristic method's performance. By the evaluation of the result, we can see that the modified methods produce a shorter maximum flow - time than the original methods.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.19 no.39
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• pp.275-284
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• 1996

It can be made a definition that scheduling is a imposition of machinery and equipment to perform a collection of tasks. Ultimately scheduling is an assessment of taking order for which would be perform. So it is called "sequencing" in other words. In a job shop scheduling, the main object is to making delivery in accordance with the due date and order form customer, not to producing lots of quantity with minimizing mean flow time in a given time. Actually, in a company, they concentrate more in the delivery than minimizing the mean flow time. Therefore this paper suggest a new priority dispatching rule under consideration as below in a n/m job shop scheduling problem with due date. 1. handling/transportation time, 2. the size of customer order With this algorithm, we can make a scheduling for minimizing the tardiness of delivery which satisfy a goal of production.roduction.