• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.7
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• pp.1390-1406
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• 1994

This study deals with the DMCLP(Delay constrained Minimum Cost Loop Problem)-one of problems arising in the design of local access computer networks. The problem consists of finding a set of rings to satisfy the traffic requirements of end user terminals. In the problem, the objective is to minimize the total link cost. This paper presents heuristic algorithm which consists of two phases for this problem, under the constraints that the number of nodes served by a single ring is limited and network mean delay is dropped within the desired time. The algorithm is derived using the clusters obtained by the existing MCLP(Minimum Cost Loop Problem) algorithm and a trade-off criterion explained in the paper. Actually, simulation results in that the proposed algorithm in this paper produces better solution than the existing MCLP algorithm modified. In addition, the algorithm has the relatively short running time.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.4
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• pp.147-152
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• 2016

One of major issues in machine learning that extracts and acquires knowledge implicit in data is to find an appropriate way of representing it. Knowledge can be represented by a number of structures such as networks, trees, lists, and rules. The differences among these exist not only in their structures but also in effectiveness of the models for their problem solving capability. In this paper, we propose partition utility as a criterion function for clustering that can lead to simplification of the model and thus avoid overfitting problem. In addition, a heuristic is proposed as a way to construct balanced hierarchical models.

• Advances in Computational Design
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• v.2 no.4
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• pp.313-331
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• 2017

In this study, teaching-learning based optimization (TLBO) is improved by incorporating model of multiple teachers, adaptive teaching factor, self-motivated learning, and learning through tutorial. Modified TLBO (MTLBO) is applied for simultaneous topology, shape, and size optimization of space and planar trusses to study its effectiveness. All the benchmark problems are subjected to stress, displacement, and kinematic stability constraints while design variables are discrete and continuous. Analyses of unacceptable and singular topologies are prohibited by seeing element connectivity through Grubler's criterion and the positive definiteness. Performance of MTLBO is compared to TLBO and state-of-the-art algorithms available in literature, such as a genetic algorithm (GA), improved GA, force method and GA, ant colony optimization, adaptive multi-population differential evolution, a firefly algorithm, group search optimization (GSO), improved GSO, and intelligent garbage can decision-making model evolution algorithm. It is observed that MTLBO has performed better or found nearly the same optimum solutions.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.26 no.3
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• pp.58-66
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• 2003

The cut tree approach of Montreuil and Ratliff [16] and eigenvector approach [10] are used to automatically draw a feasible facility layout with aisle structure. The department arrangement can minimize an aisle distance criterion considering door locations and dimension constraints. The aisle distance is measured by the door to door distance between departments. An eigenvector and cut tree approaches [1] are implemented based on the branch and bound technique in Kim et al. [2] in order to obtain feasible layouts. Then, the algorithm to fix the door location of each department is developed. After the door locations are determined, the factory layout is evaluated in terms of aisle distance. The aisle structure is obtained by expanding the original layout. The solution is kept until we will find better factory layout. The proposed approach based on the branch and bound technique, in theory, will provide the optimal solution. If the runs are time and/or node limited, the proposed method is a strong heuristic. The technique is made further practical by the fact that the solution is constrained such that the rectangular shape dimensions length(l) and width(w) are fixed and a perfect fit is generated if a fit is possible.

• The Transactions of the Korea Information Processing Society
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• v.2 no.6
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• pp.823-830
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• 1995

A reactive piloting policy for Flexible Assembly Lines (FAL) is proposed, where the sequencing of the operations as well as the assignment of tasks to manipulators are not predetermined but driven by the actual state of the FAL For all work-in-process coming from a manipulator, the next destination is determined by minimizing a temporal criterion taking into account the time needed to reach the destination, the load of the manipulator to reach, the durati on of the operation to be completed in the destination manipulator, and the availability of product components in this manipulator. The purpose of proposed piloting policy is to manufacture a given quantity of products as rapidly as possible by balancing the amount of work allocated to manipulators and to reduce the efforts required for scheduling the production of short series of diversified products. After introducing the characteristics of assembly processes and FAL modelization, the proposed algorithm is evaluated by simulations. The simulations of the proposed algorithm showed satisfactory results.

• Journal of Korean Institute of Industrial Engineers
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• v.29 no.1
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• pp.49-64
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• 2003

Although assembly sequence planning is an essential task in assembly process planning, it is known as one of the most difficult and time consuming jobs because its complexity is increased geometrically when the number of parts in an assembly is increased. The purpose of this study is to develop a more efficient algorithm for generating assembly sequences automatically. By considering subassemblies, a new heuristic method generates a preferred parallel assembly sequence that can be used in robotic assembly systems. A parallel assembly sequence concept provides a new representation scheme for an assembly in which the assembly sequence precedence information is not required. After an user inputs both the directional mating relation information and the mating condition information, an assembly product is divided into subgroups if the product has cut-vertices. Then, a virtual disassembly process is executed to generate alternate parallel assembly sequences with intermediate assembly stability. Through searching parts relations in the virtual disassembly process, stable subassemblies are extracted from translation-free parts along disassembling directions and this extraction continues until no more subassemblies are existed. Also, the arithmetic mean parallelism formula as a preference criterion is adapted to select the best parallel assembly sequence among others. Finally a preferred parallel assembly sequence is converted to an assembly BOM structure. The results from this study can be utilized for developing CAAPP(Computer-Aided Assembly Process Planning) systems as an efficient assembly sequence planning algorithm.

• Journal of KIISE:Software and Applications
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• v.31 no.3
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• pp.293-307
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• 2004

We consider the problem of scheduling tasks of a precedence constrained task graph, where each task has its execution time and deadline, onto a set of identical processors in a way that simultaneously minimizes the number of processors required and the total tardiness of tasks. Most existing approaches tend to focus on the minimization of the total tardiness of tasks. In another methods, solutions to this problem are usually computed by combining the two objectives into a simple criterion to be optimized. In this paper, the minimization is carried out using a multiobjective genetic algorithm (GA) that independently considers both criteria by using a vector-valued cost function. We present various GA components that are well suited to the problem of task scheduling, such as a non-trivial encoding strategy. a domination-based selection operator, and a heuristic crossover operator We also provide three local improvement heuristics that facilitate the fast convergence of GA's. The experimental results showed that when compared to five methods used previously, such as list-scheduling algorithms and a specific genetic algorithm, the Performance of our algorithm was comparable or better for 178 out of 180 randomly generated task graphs.