• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.163.3-163
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• 2001

This paper presents the two-step strategy method of performing optimal scheduling of paper mill processes using MINLP (Mixed-Integer Non-Linear Programming) considering the trim loss problem in sheet cutting processes. The mathematical model for a sheet cutting process in the form of MINLP is developed in this study, and minimizing total cost is performed considering the cost of raw paper roll, :hanging cutting patterns, storage of over-product and recycling/burning trim. The paper has been used to deliver and conserve information for a long time, and it is needed to have various sizes and weights ...

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.2
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• pp.260-267
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• 2007

Systematic studies on the dispatch scheduling algorithm can enhance the efficiency of electricity market operation. In addition, as the dispatching policies in competitive electricity markets directly affect the market participants' profits, the dispatch scheduling procedure should be reasonable, systematic, and transparent. In this paper, we propose an unconstrained/constrained pre-dispatch scheduling algorithm and develop corresponding programs applicable to wholesale electricity markets.

• Journal of the Korean Operations Research and Management Science Society
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• v.14 no.2
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• pp.19-26
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• 1989

We in this paper have defined the concept of .epsilon.-symmetric relation between the Lagrangean relaxation and the Benders' decomposition. This links the solutions of the Lagrangean subproblems and those of the Benders' subproblems even under positive duality gaps. As an application we have discussed the reduction of the size for a special class of problems.

• Journal of Korean Institute of Industrial Engineers
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• v.11 no.2
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• pp.29-37
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• 1985

This paper studies a production-inventory model which unifies the inventory problem of raw materials and the finished product for a single product manufacturing system. The integrated production-inventory model is formulated wth a nonlinear mixed integer programming problem. An algorithm is developed by utilizing the finite explicit enumeration method. The algorithm guarantees to generate an optimal policy for minimizing the total annual variable cost. A mumerical example involving 15 raw materials is given to illustrate the recommended solution procedure.

• Journal of the Korean Operations Research and Management Science Society
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• v.18 no.2
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• pp.131-145
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• 1993

This paper deals with scheduling problem of the chemical process system where aircraft parts go through a given sequence of tanks filled with chemical solutions. The system has two hoists which move carriers holding the parts between tanks. A mixed integer programming model is developed from which a maximum throughput schedule can be found for the hoist movements. To show the validity of the model, a real world problem is solved and the results are compared with those with an existing approach.

• Journal of Communications and Networks
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• v.13 no.1
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• pp.26-31
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• 2011

In this paper, we formulate the minimum power multicast problem in wireless networks as a mixed integer linear programming problem and then propose a Lagrangean relaxation based algorithm to solve this problem. By leveraging on the information from the Lagrangean multiplier, we could construct more power efficient routing paths. Numerical results demonstrate that the proposed approach outperforms the existing approaches for broadcast, multicast, and unicast communications.

• Journal of Korean Society of Transportation
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• v.10 no.3
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• pp.75-102
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• 1992

지난 수십년간 수많은 신호교차로제어모형이 제시되어 왔으나 과포화교차로를 특별히 다루는 기법은 거의 없었다. 본고에서는 과포화상태의 신호교차로제어를 위한 최적화모형이 제시된다. 지체도최소화나 연동폭최대화가 전통적인 제어목표로 사용되어 왔으나 혼잡교차로 제어에는 생산성최대화(maximum productivity)가 적절하며 본 모형에 사용되었다. 제시된 최적화모형은 Mixed Integer Linear Programming의 형태를 취한다. 본 모형은 두 개의 교차로 문제에 적용되었으며, 모형화 과정에 사용된 가정들의 적절함이 민감도분석에 의해 증명되었다. 최적해의 검증을 위하여 microscopic simulation model인 TRAF-NETSIM을 사용하였다.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.12 no.19
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• pp.79-88
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• 1989

This characteristics of process industries are high capital intensity, relatively long and sequence dependent setup times, and extremely limited capacity resources. The lot sizing, sequencing and limited capacity resources factors must he considered for production scheduling in these industries. This paper presents a mixed integer programming model for production scheduling. The economic trade offs between capacitated lot sizing flow shop scheduling and sequence dependent setup times also be compared with SMITH-DANIELS's model. As a results, it is shown that this paper has lower total cost, more efficient throughput than SMITH-DANIELS's model.

• 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.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.170-174
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• 2003

In this research, we consider an integrated manufacturing/distribution planning problem in supply chain (SC) which has non-integer time lags. We focus on a capacitated manufacturing planning and capacity allocation problem for the system. We develop a mixed binary integer linear programming (MBLP) model and propose an efficient heuristic procedure using an adaptive genetic algorithm, which is composed of a regeneration procedure for evaluating infeasible chromosomes and the reduced costs from the LP-relaxation of the original model. The proposed an adaptive genetic algorithm was tested in terms of the solution accuracy and algorithm speed during numerical experiments. We found that our algorithm can generate the optimal solution within a reasonable computational time.