• Asia pacific journal of information systems
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• v.1 no.1
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• pp.49-62
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• 1991

This paper examines the problems of database partitioning and file allocation in a fixed topology distributed computer network. The design objective is to make files as collections of attributes and to allocate these files to network nodes so that a minimum total transmission cost is achieved subject to storage capacity constraints. A mathematical model for solving the problem is formulated and, the resulting optimization problem is shown to fall in a class of NP-complete problems. A new heuristic algorithm is developed which uses the idea of allocating attributes according to the transaction requirements at each computer node and then making files using the allocated attributes. Numerical results indicate that the heuristic algorithm yields practicable low cost solutions in comparison with the existing methods which deal with the file allocation problems and database partitioning problems independently.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.2
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• pp.79-86
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• 2020

To make a satisfactory decision regarding project scheduling, a trade-off between the resource-related cost and project duration must be considered. A beneficial method for decision makers is to provide a number of alternative schedules of diverse project duration with minimum resource cost. In view of optimization, the alternative schedules are Pareto sets under multi-objective of project duration and resource cost. Assuming that resource cost is closely related to resource leveling, a heuristic algorithm for resource capacity reduction (HRCR) is developed in this study in order to generate the Pareto sets efficiently. The heuristic is based on the fact that resource leveling can be improved by systematically reducing the resource capacity. Once the reduced resource capacity is given, a schedule with minimum project duration can be obtained by solving a resource-constrained project scheduling problem. In HRCR, VNS (Variable Neighborhood Search) is implemented to solve the resource-constrained project scheduling problem. Extensive experiments to evaluate the HRCR performance are accomplished with standard benchmarking data sets, PSPLIB. Considering 5 resource leveling objective functions, it is shown that HRCR outperforms well-known multi-objective optimization algorithm, SPEA2 (Strength Pareto Evolutionary Algorithm-2), in generating dominant Pareto sets. The number of approximate Pareto optimal also can be extended by modifying weight parameter to reduce resource capacity in HRCR.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.16 no.4
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• pp.225-237
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• 2016

In conventional transportation problem (TP), all the parameters are always certain. But, many of the real life situations in industry or organization, the parameters (supply, demand and cost) of the TP are not precise which are imprecise in nature in different factors like the market condition, variations in rates of diesel, traffic jams, weather in hilly areas, capacity of men and machine, long power cut, labourer's over time work, unexpected failures in machine, seasonal changes and many more. To counter these problems, depending on the nature of the parameters, the TP is classified into two categories namely type-2 and type-4 fuzzy transportation problems (FTPs) under uncertain environment and formulates the problem and utilizes the trapezoidal fuzzy number (TrFN) to solve the TP. The existing ranking procedure of Liou and Wang (1992) is used to transform the type-2 and type-4 FTPs into a crisp one so that the conventional method may be applied to solve the TP. Moreover, the solution procedure differs from TP to type-2 and type-4 FTPs in allocation step only. Therefore a simple and efficient method denoted by PSK (P. Senthil Kumar) method is proposed to obtain an optimal solution in terms of TrFNs. From this fuzzy solution, the decision maker (DM) can decide the level of acceptance for the transportation cost or profit. Thus, the major applications of fuzzy set theory are widely used in areas such as inventory control, communication network, aggregate planning, employment scheduling, and personnel assignment and so on.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.36 no.9
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• pp.609-615
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• 1987

The optimal operation of power system is developed by alternately using real power dispatch and reactive power dispatch problem. The real power system scheduling process is formulated as an optimization problem with linear inequality constraints. A.C. loadflow method is used for the problem solution and line losses are considered. The constraints under consideration are generator power limits, load scehdling limits and line capacity limits. In solving the objective function the Dual Relaxation method is adopted. Tests indicate that the method is practical for real time application. The reactive power control problem uses the Dual Simplex Relaxation method as in the real scheduling case. Insted of minimizing the cost of power system, the objective is selected as to determine the highest possible voltage schedule. The constraints under consideration are the voltage limits at each node and the possibilities of supply or absobtion of reactive energy by generator units and the compensation facilities. Tests indicate that the method is practical for real time applications. The overall optimization methods developed in this paper proved to obtained fine results in minimizing object function compared with the method without using voltage control. And the overall voltage profiles were also improved.

• Design & Manufacturing
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• v.2 no.3
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• pp.28-31
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• 2008

In recent, the demand of high-productivity injection mold is increased because of the growth of international packaging market which is induced by an increase of population. The increase of productivity leads to the large-capacity injection molding machine and peripheral devices. For solving this problem, the stack mold which is based on the exsiting machine and device has researched in advanced countries actively. In this paper, as the preliminary research of stack mold development, the stack mold which has 2 level ${\times}4$ cavity was designed and fabricated. Besides, the motion and structural analysis were performed to verify the stability of developed stack mold.

• Health Policy and Management
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• v.17 no.4
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• pp.54-81
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• 2007

The paradigm of health promotion requests community participation and its active problem-solving. Community is conceptualized as a resource pool to be organized. Such resource is called community capacity. Community participation is a process of capacity building. Community voluntary associations are considered as valuable resource to be used for health promotion. This paper tried to identify the network structure among community voluntary associations and to infer the possibility to make such network of organizations participate in health promotion programs. Two survey data were used for this research: 1) Measurements and Evaluations of Community Capacity on Dobong-gu (N=94) 2) A development plan of health medicine service to be Healthy Gangdong-gu (N=69). The questionnaire included such variables measuring community capacity as leadership, membership, organizational resources, and inter-organizational network, etc. Both regions had the following common characteristics: 1) There were positive correlations between the organization's budget and membership. 2) Organizational types were associated with their founded years. Two regions showed the following differences: Dobong displayed the high density of community organizations, but Gangdong showed the low density. Dobong community organizations were able to be classified into three network clusters such as women & environments, youth & adolescent, and sports organizations. Each cluster of organizations favored the different type of health promotion programs. Gangdong community organizations were less developed, and not possible to be clustered. Depending upon the level of community capacity or community organizations' differentiation, the strategy of community participation could be settle down in different ways. Particularly the health agency had to pay more attention to support the growth of civil organizations.

• Industrial Engineering and Management Systems
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• v.13 no.4
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• pp.369-382
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• 2014

This paper introduces a new multi-product multi-period multi-objective aggregate production planning problem. The proposed problem is modeled using multi-objective mixed-integer mathematical programming. Three objective functions, including minimizing total cost, maximizing customer services level, and maximizing the quality of end-product, are considered, simultaneously. Several constraints such as quantity of production, available time, work force levels, inventory levels, backordering levels, machine capacity, warehouse space and available budget are also considered. Some parameters of the proposed model are assumed to be qualitative and modeled using fuzzy sets. Then, a fuzzy goal programming approach is proposed to solve the model. The proposed approach is applied on a real-world industrial case study of a color and resin production company called Teiph-Saipa. The approach is coded using LINGO software. The efficacy and applicability of the proposed approach are illustrated in the case study. The results of proposed approach are compared with those of the existing experimental methods used in the company. The relative dominance of the proposed approach is revealed in comparison with the experimental method. Finally, a data dictionary, including the way of gathering data for running the model, is proposed in order to facilitate the re-implementation of the model for future development and case studies.

• Journal of Korean Institute of Industrial Engineers
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• v.22 no.3
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• pp.485-498
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• 1996

For a tree T rooted at a concentrator location in a telecommunication system, we assume that the capacity H for the concentrator is given and a profit $c_v$, and a demand $d_v$, on each node $\upsilon$ of T are also given. Then, the capacitated subtree of a tree problem (CSTP) is to find a subtree of T rooted at the concentrator location so as to maximize the total profit, the sum of profits over the subtree, under the constraint satisfying that the sum of demands over the subtree does not exceed H. In this paper, we develop a pseudopolynomial-time algorithm for CSTP, the depth-first dynamic programming algorithm. We show that a CSTP can be solved by our algorithm in $\theta$ (nH) time, where n is the number of nodes in T. Our algorithm has its own advantage and outstanding computational performance incomparable with other approaches such as CPLEX, a general integer programming solver, when it is incorporated to solve a Local Access Telecommunication Network design problem. We report the computational results for the depth-first dynamic programming algorithm and also compare them with those for CPLEX. The comparison shows that our algorithm is competitive with CPLEX for most cases.

• IE interfaces
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• v.25 no.2
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• pp.264-275
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• 2012

The process of semiconductor(IC Package) manufacturing usually includes lots of complex and sequential processes. Many kinds of equipments are installed with the mixed concept of serial and parallel manufacturing system. The business environments of the semiconductor industry have been changed frequently, because new technologies are developed continuously. It is the main reason of new investment plan and layout consideration. However, it is difficult to change the layout after installation, because the major equipments are expensive and difficult to move. Furthermore, it is usually a multiple-objective problem. Thus, new investment or layout change should be carefully considered when the production environments likewise product mix and production quantity are changed. This paper introduces a simulation case study of a Korean company that produces packaging substrates(especially lead frames) and requires multi-objective decision support. $QUEST^{(R)}$ is used for simulation modelling and AHP(Analytic Hierarchy Process) and DEA(Data Envelopment Analysis) are used for weighting of qualitative performance measures and solving multiple-objective layout problem, respectively.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.1
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• pp.216-239
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• 2021

The present work addresses the challenging problem of coordinating power allocation with interference management in multi-robot networks by applying the promising expansion capabilities of multiple-input multiple-output (MIMO) and full duplex systems, which achieves it for maximizing the throughput of networks under the impacts of Doppler frequency shifts and external jamming. The proposed power allocation with interference coordination formulation accounts for three types of the interference, including cross-tier, co-tier, and mixed-tier interference signals with cluster head nodes operating in different full-duplex modes, and their signal-to-noise-ratios are respectively derived under the impacts of Doppler frequency shifts and external jamming. In addition, various optimization algorithms, including two centralized iterative optimization algorithms and three decentralized optimization algorithms, are applied for solving the complex and non-convex combinatorial optimization problem associated with the power allocation and interference coordination. Simulation results demonstrate that the overall network throughput increases gradually to some degree with increasing numbers of MIMO antennas. In addition, increasing the number of clusters to a certain extent increases the overall network throughput, although internal interference becomes a severe problem for further increases in the number of clusters. Accordingly, applications of multi-robot networks require that a balance should be preserved between robot deployment density and communication capacity.