• Journal of Korean Institute of Industrial Engineers
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• v.11 no.2
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• pp.141-154
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• 1985

The capacity expansion problem has been defined. Existing literatures on capacity expansion problems have been reviewed and unified under a structure of problem domain. The problem domain has been defined by three relavent coordinates; function or objective of the project, consideration of resource allocation, and consideration of project sequencing. Long range planning is of vital importance in setting up ultimately efficient capital investment plans to meet immediate demand increase. Simplified expansion sequencing example problems have been introduced and solved to help understanding of a solution scheme.

• Journal of the military operations research society of Korea
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• v.11 no.2
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• pp.15-22
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• 1985

Planning for the expansion of production capacity is of vital importance in many applications within the private and public sectors. This paper considers a sequencing expansion problem in which capacity can be added only at discrete points in time. Given the demand forecast of each period, capacity and cost of each expansion project, we are to determine the sequence of expansion necessary to provide sufficient capacity to meet the demand in all periods at minimum cost. This problem is formulated as a pure integer programming and solved by branch and bound method using Lagrangian relaxation. At first, simple sequencing expansion problem is presented, and in the latter part, extension to include precedence between projects is suggested.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.33 no.1
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• pp.71-79
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• 2010

This paper addresses capacity expansion planning model of distribution center under usability of public distribution center. For discrete and finite time periods, demands for distribution center increase dynamically. The capacity expansion planning is to determine the capacity expansion size of private distribution center and usage size of public distribution center for each period through the time periods. The capacity expansion of private distribution center or lease usage of public distribution center must be done to satisfy demand increase for distribution center. The costs are capacity expansion cost and excess capacity holding cost of private distribution center, lease usage cost of public distribution center. Capacity expansion planning of minimizing the total costs is mathematically modelled. The properties of optimal solution are characterized and a dynamic programming algorithm is developed. A numerical example is shown to explain the problem.

• Journal of Electrical Engineering and Technology
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• v.10 no.4
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• pp.1460-1470
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• 2015

This paper presents an approach to solve the long-term generation expansion planning problem of the restructured electricity industry using an agent-based environment. The proposed model simulates the generation investment decisions taken by a particular agent (i.e. a generating company) in a market environment taking into account its competitors’ strategic investment. The investment decision of a particular company is modeled taking into account that such company has imperfect foresight on the future system development hence electricity prices. The delay in the construction of new plants is also explicitly modeled, in order to compute accurately the yearly revenues of each agent. On top of a conventional energy market, several capacity incentive mechanisms including capacity payment and capacity market are simulated, so as to assess their impact on the investment promotion for generation expansion. Results provide insight on the investment cycles as well as dynamic system behavior of long-term generation expansion planning in a competitive electricity industry.

• ETRI Journal
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• v.15 no.3
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• pp.47-59
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• 1994

A capacity expansion planning problem with buy-or-lease decisions is considered. Demands for capacity are deterministic and are given period-dependently at each period. Capacity additions occur by buying or leasing a capacity, and leased capacity at any period is reconverted to original source after a fixed length of periods, say, lease period. All cost functions (buying, leasing and idle costs) are assumed to be concave. And shortages of capacity and disposals are not considered. The properties of an optimal solution are characterized. This is then used in a tree search algorithm for the optimal solution and other two algorithms for a near-optimal solution are added. And these algorithms are illustrated with numerical examples.

• 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.

• Journal of the Korean Operations Research and Management Science Society
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• v.31 no.3
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• pp.81-96
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• 2006

We consider a rental company that dynamically manages Its capacity level through capacity addition and return While serving customer with its own capacity, the company expands its capacity by renting items from an outside source so that it can avoid lost opportunities of rental which occur when stock is not sufficient. If stock becomes sufficiently large enough to cope with demands, the company returns expanded capacity to the outside source. Formulating the model into a Markov decision problem, we identify an optimal capacity management Policy which states when the company should expand its capacity and when it should return expanded capacity after capacity addition. Since it is intractable to analytically find the optimal capacity management policy and the optimal size of capacity expansion, we present a numerical procedure that finds these optimal values based on the value iteration method. Numerical analysis is implemented and we observe monotonic properties of the optimal performance measures by system parameters, which are meaningful in developing effective heuristic policies.

• Geotechnical Engineering
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• v.5 no.1
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• pp.35-46
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• 1989

To analyse the end bearing capacity of a single pile in cohesionless soils, the mode of deformation due to a pile penetration has been intestigated through model pile penetration tests using acetone hardening and resin impregnation technique. A new mode of deformation has been assumed from the experimental results and a new solution compeying with the theory of spherical cal.its expansion has been proposed. The end bearing capacity according to the proposed solution is expressed as the product of the limit spherical cavity expansion pressure multiplied by a col.relation factor. The results has been compared with other solutions based on the theory of cavity expansion. From the comparison, the proposed solution is expected to provide a way to solve the problem of pile bearing capacity prediction based on the theory of cavity expansion which often has been criticized as giving higher value of pile bearing capacity than the actual value.

• Journal of Korean Institute of Industrial Engineers
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• v.12 no.1
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• pp.81-94
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• 1986

A shortest path dynamic programming formulation is proposed and attemped to solve an uncapacitated expansion sequencing problem. It is also compared with the Extended Binary State Space approach with total capacity. Difficulties and merits associated with the formulation are discussed. The shortest path dynamic programming lacks the separability condition and an optimal solution is not guaranteed. However it has other merits and seems to be the practical solution procedure for the expansion sequencing problem in a sense that it finds near optimal solution with less state evaluations.

• The Journal of Information Systems
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• v.29 no.1
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• pp.75-91
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• 2020

Purpose Retrofit, defined to be addition of new technologies or features to the old system to increase efficiency or to abate GHG emissions, is considered as an important alternative for the old coal-fired power plant. The purpose of this study is to propose mathematical method to model multiple alternative retrofit in Generation Capacity Expansion Planning(GCEP) problem, and to get insight to the retrofit patterns from realistic case studies. Design/methodology/approach This study made a multi-alternative retrofit GECP model by adopting some new variables and equations to the existing GECP model. Added variables and equations are to ensure the retrofit feature that the life time of retrofitted plant is the remaining life time of the old power plant. We formulated such that multiple retrofit alternatives are simultaneously compared and the best retrofit alternative can be selected. And we found that old approach to model retrofit has a problem that old plant with long remaining life time is retrofitted earlier than the one with short remaining life time, fixed the problem by some constraints with some binary variables. Therefore, the proposed model is formulated into a mixed binary programming problem, and coded and run using the GAMS/cplex. Findings According to the empirical analysis result, we found that approach to model the multiple alternative retrofit proposed in this study is comparing simultaneously multiple retrofit alternatives and select the best retrofit satisfying the retrofit features related to the life time. And we found that retrofit order problem is cleared. In addition, the model is expected to be very useful in evaluating and developing the national policies concerning coal-fired power plant retrofit.