• Journal of KIISE:Computing Practices and Letters
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• v.6 no.2
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• pp.216-224
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• 2000

The spatial layout planning system allocates rectangular resources in the limited space according to user requirements, This system also can optimizes the spatial allocation problem to maximize the user's requirement. The spatial layout planning Problems for this system can be solved by searching a wide area of space since this problem entails the non-polynomial algorithm. By accommodating the user's dynamic requirements, the modification of a specific space and the redesign of the whole area can be accomplished. In this paper, the spatial layout planning problem is solved efficiently with a resource allocation method based on CSP. The dynamic constraints by adding user requirements are accommodated through the intelligent user Interface. The 3-D layout on the web environment by using VRML is also shown for providing for the visual verification of the 2-D layout and, thereafter, the additional modification of the 2-D layout.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.04a
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• pp.465-468
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• 1996

We deal with facility layout problems with shape constraints. A simulated annealing algorithm is developed for the problems. In the algorithm, a solution is encoded as a matrix that has information about relative locations of the facilities in the floor. A block layout is constructed by partitioning the floor into a set of rectangular blocks according to the information while satisfying areas of facilities. In this paper, three methods are suggested for the partitioning procedure and they are employed in the simulated annealing algorithm. Results of computational experiments show that the proposed algorithm performs better than existing algorithms, especially for problems with tight shape constraints.

• Journal of the Korean Society of Safety
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• v.35 no.1
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• pp.25-33
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• 2020

In most plant layout optimization researches, MILP(Mixed Integer Linear Programming) problems, in which the objective function includes the costs of pipelines connecting process equipment and cost associated with safety issues, have been employed. Based on these MILP problems, various optimization solvers have been applied to investigate the optimal solutions. To consider safety issues on the objective function of MILP problems together, the accurate information about the impact and the frequency of potential accidents in a plant should be required to evaluate the safety issues. However, it is really impossible to obtain accurate information about potential accidents and this limitation may reduce the reliability of a plant layout problem. Moreover, in real industries such as plant engineering companies, the plant layout is previously fixed and the considerations of various safety instruments and systems have been performed to guarantee the plant safety. To reflect these situations, the two step optimization problems have been designed in this study. The first MILP model aims to minimize the costs of pipelines and the land size as complying sufficient spaces for the maintenance and safety. After the plant layout is determined by the first MILP model, the optimal locations of blast walls have been investigated to maximize the mitigation impacts of blast walls. The particle swarm optimization technique, which is one of the representative sampling approaches, is employed throughout the consideration of the characteristics of MILP models in this study. The ethylene oxide plant is tested to verify the efficacy of the proposed model.

• Journal of the Korean Operations Research and Management Science Society
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• v.20 no.1
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• pp.63-81
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• 1995

This paper presents a model and algorithm for solving the multi-factor plant layout problem. The model can incorporate more than two factors that may be either quantitative or qualitative. The algorithm is based on simulated annealing, which has been successfully applied for the solution of combinatorial problems. A set of problems previously used by various authors is solved to demonstrate the effectiveness of the proposed methods. The results indicate that the proposed methods can yield good quality for each of eleven test problems.

• Transactions of the Korean Society of Mechanical Engineers
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• v.17 no.12
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• pp.3063-3072
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• 1993

The layout is an important and difficult problem in industrial applications like sheet metal manufacturing, garment making, circuit layout, plant layout, and land development. The module layout problem is known to be non-deterministic polynomial time complete(NP-complete). To efficiently find an optimal layout from a large number of candidate layout configuration a heuristic algorithm could be used. In recent years, a number of researchers have investigated the combinatorial optimization problems by using neural network principles such as traveling salesman problem, placement and routing in circuit design. This paper describes the application of Self-organizing Feature Maps(SOM) of the Kohonen network and Simulated Annealing Algorithm(SAA) to the layout problem of the two-dimensional rectangular shapes.

• Journal of the Korea Society for Simulation
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• v.10 no.2
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• pp.1-14
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• 2001

The layout design of component plays an important role in the design and usability of many engineering products. The Engineering artifacts of today are becoming increasingly complicated. The simulated annealing method has been applied effectively to the layout and packing problems of wafer. The main characteristics of simulated annealing method is that an optimum can be obtained from the many local optimums by controlling the temperature and introducing the statistic flickering. The objective of this study is to suggest a method to apply the simulated annealing method to the three dimensional layout design of submergible boat which has multiple constraint conditions and evaluation criteria. We describe an approach to define cost function, constraints and generate layouts using a computer. In this research three dimensional LAYout Design Optimization Program(LAYDOP ver.2) has been developed. The layout result(the total value of evaluation criteria) designed by a human layout expert has been improved by 31.0% using this program.

• Journal of Korean Institute of Industrial Engineers
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• v.23 no.2
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• pp.359-370
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• 1997

We consider a facility layout problem with the objective of minimizing total transportation distance, which is the sum of rectilinear distances between facilities weighted by the frequency of trips between the facilities. It is assumed that facilities are required to have rectangular shapes and there is no empty space between the facilities in the layout. In this study, a graph theoretic heuristic is developed for the problem. In the heuristic, planar graphs are constructed to represent adjacencies between the facilities and then the graphs are converted to block layouts on a continual plane using a layout construction module. (Therefore, each graph corresponds to a layout.) An initial layout is obtained by constructing a maximal weighted planar graph and then the layout is improved by changing the planar graph. A simulated annealing algorithm is used to find a planar graph which gives the best layout. To show the performance of the proposed heuristic, computational experiments are done on randomly generated test problems and results are reported.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.22 no.49
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• pp.89-98
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• 1999

The objective of this study is to develop an improved algorithm for layout problems. Computerized facility layout program was also applied to solve the layout problem in locomotive maintenance workshop. The current facility layout is structured in the large space without considerations of many variable factors. For this reason, effectiveness of layout results in loss on effective space utility. This study is to develop an algorithm in the consideration of importance weight and desirable shape of specific department in the computerized layout planning and quantitative relationship rating between each department was used. Standard process duration of locomotive maintenance workshop was used to select the main activities of locomotive maintenance work. This study could generate more efficient facility layout design to reduce the number of movement frequency and travel distance in maintenance workshop.

• Korean Management Science Review
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• v.14 no.1
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• pp.67-76
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• 1997

The most research on facility layout problems ignored the actual shapes of activity spaces and the aisles between activities. In many cases, the research also ignored the actual shape of building where the activities are to be arranged. In this paper, We present a block based layout technique that applies a genetic algorithm to search for a very good facility layout with horizontal aisles. From the extensive experiments for two different cases with respect to the shape of activity space, it was found that the proposed method generated better layouts than the ones obtained by applying Tam's algorithm in all test problems. The proposed algorithm showed about 10% improvement of performance on the average. We determined the best combination of the reproduction rule and the genetic operators with their probabilities for each test problem through the experiment.

• Journal of Korea Society of Industrial Information Systems
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• v.13 no.5
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• pp.142-148
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• 2008

Facility Layout Planning is concerned with how to arrange facilities necessary for production in a given space. Its objective is often to minimize the total sum of all material flows multiplied by the distance among facilities. FLP belongs to NP complete problem; i.e., the number of possible layout solutions increases with the increase of the number of facilities. Thus, meta heuristics such as Genetic Algorithm (GA) and Simulated Annealing have been investigated to solve the FLP problems. However, one of the biggest problems which lie in the existing meta heuristics including GA is hard to find an appropriate combinations of parameters which result in optimal solutions for the specific problem. The Ant System algorithm with elitist and ranking strategies is used to solve the FLP problem as an another good alternative. Experimental results show that the AS algorithm is able to produce the same level of solution quality with less sensitive parameters selection comparing to the ones obtained by applying other existing meta heuristic algorithms.