• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1758-1761
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• 1997

The problem of long range capacity expansion planing for chemical processing network under uncertain demand forecast secnarios is addressed. This optimization problem involves capactiy expansion timing and sizing of each chemical processing unit to maximize the expected net present value considering the deviation of net present values and the excess capacity over a given time horizon. A multiperiod mixed integer nonlinear programming optimization model that is both solution and modle robust for any realization of demand scenarios is developed using the two-stage stochastic programming algorithm. Two example problems are considered to illustrate the effectiveness of the model.

• Korean Management Science Review
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• v.11 no.1
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• pp.91-106
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• 1994

In mixed model assembly lines, products are assembled seqeuntially that have different combination of options specified by customers. In just in time (JIT) environment, production smoothing becomes an important issue for sub-lines which supply the necessary parts to each workstation of the assembly line. Another important issue is to avoid line stopping caused by work overload in workstations. To find a sequence which minimizes the costs associated with line stoppage and the option parts inventory level, a nonlinear mixed integer programming is formulated. Recognizing the limit of the Branch and Bound technique in large sized problems, a heuristic solution procedure is proposed. The performance of the heuristic is compared with the Branch and Bound technique through randomly generated test problems. The computational results indicate that on the average the heuristic solutions deviate approximately 3.6% from the optimal solutions.

• Journal of Electrical Engineering and Technology
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• v.12 no.1
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• pp.53-63
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• 2017

The increasing of wind power penetration level presents challenges in classical optimal reactive power dispatch (ORPD) which is usually formulated as a deterministic optimization problem. This paper proposes a two-stage stochastic programming model for ORPD by considering the uncertainties of wind speed and load in a specified time interval. To avoid the excessive operation, the schedule of compensators will be determined in the first-stage while accounting for the costs of adjusting the compensators (CACs). Under uncertainty effects, on-load tap changer (OLTC) and generator in the second-stage will compensate the mismatch caused by the first-stage decision. The objective of the proposed model is to minimize the sum of CACs and the expected energy loss. The stochastic behavior is formulated by three-point estimate method (TPEM) to convert the stochastic programming into equivalent deterministic problem. A hybrid Genetic Algorithm-Interior Point Method is utilized to solve this large-scale mixed-integer nonlinear stochastic problem. Two case studies on IEEE 14-bus and IEEE 118-bus system are provided to illustrate the effectiveness of the proposed method.

• Journal of the Korean Operations Research and Management Science Society
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• v.18 no.1
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• pp.1-18
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• 1993

The family disaggregation model of hierarchical production planning (HPP) is the problem of (0 -1) mixed integer programming that minimizes the total sum of setup costs and inventory holding costs over the planning horizon. This problem is hard in a practical sense since optimal solution algorithms have failed to solve it within reasonable computation times. Thus effective familoy disaggregation algorithm should be developed for HPP. The family disaggregation algorithm developed in this paper consists of the first stage of finding initial solutions and the second stage of improving initial solutions. Some experimental results are given to verify the effectiveness of developed disaggregation algorithm.

• Proceedings of the KIEE Conference
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• 2005.11b
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• pp.174-176
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• 2005

The introduction of competition in the electricity market requires a new paradigm in the capacity planning. This paper presents a methodology on a transmission planning considering dispatch in the government view point. The proposed model is mixed integer programming that minimized operation and construction costs. The proposed idea is exorcised on a case study.

• 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 ...

• 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 Korea Water Resources Association
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• v.35 no.1
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• pp.37-49
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• 2002

The application of conventional method for optimizing firm water supply and hydro-electric power generation has some limitation during abnormal or extreme drought periods. Hashimoto et al. (1982) suggested there risk evaluation criteria such as reliability, resilience, and vulnerability. These three criteria have been incorporated into a mixed-integer programming model for evaluating the possible performance of water- supply reservoir (Moy et al., 1986; Srinivasan et al., 1999). However, till now, these kind of researches have been conducted only for water-supply reservoir. Therefore there have been no other study for multi-purpose dam including hydro-electric power generation. This study presents an improved formulation of the previous model for evaluating a multi-purpose reservoir system operation considering water supply and hydro-electric power generation. The modified model was applied to the Daechung multi-purpose reservoir system in the Keum river basin to demonstrate the efficiency of the improved formulation.

• Korean Management Science Review
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• v.29 no.2
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• pp.91-103
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• 2012

Revenue management problems originated in the 1970's in the context of the airline industry have been successfully introduced in airline industries. It has started on the capacity control by booking classes for available seats, and has been recognized as a powerful tool to maximize the total revenue. Changing customer behavior and airline market environments, however, has required a new mechanism for improving the revenue. Dynamic pricing is one of innovative tools which is to adjust prices according to the market status. In this paper, we consider a dynamic pricing and seat control problem for discrete time horizon. The problem can be modeled as a stochastic programming problem. Applying the linear approximation technique and given the price set for each time, we suggest a mixed Integer Programming model to solve our problem efficiently. From the simulation results, we can find our model makes good performance and can be expanded to other comprehensive problems.

• Journal of the Korea Institute of Military Science and Technology
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• v.13 no.5
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• pp.748-758
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• 2010

Navy surface vessels require pier services such as emergency repair, oil supply, arm loading/unloading, craning, standby readiness, normal repair, gun arrangement, ammunition loading, and food loading during the period in port. The purpose of this study is to establish efficient berth allocation plan for navy surface vessels in home port under the limited resources of piers and equipments. This study suggests Mixed Integer Programming model for berth allocation problem, considering precedence relationships among services and the uncertainty of the arrival and departure for each vessel. For an effective analysis, the model is implemented by ILOG OPL(Optimization Programming Language) Studio 6.0 and ILOG CPLEX 11.1., which shows a reasonable result.