• 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.

• Proceedings of the Korea Society for Simulation Conference
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• 1992.10a
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• pp.1-1
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• 1992

This paper presents a user-oriented port expansion simulation model that determines the future economic port capacity to meet the projected demand. The model consists of two parts; a physical impact simulation, and an economic impact simulation. The first part of the model simulates the effects caused by the port capacity expansion. The second part evaluates the port economics due to changes in the port capacity. The model was validated by applying it to the actual port expansion followed at the Port of Mobile, Alabama. A case study is then presented to demonstrate the capacity of the model with a coal handling port, the McDuffie Terminals at the Port of Mobile.

• Journal of Korean Institute of Industrial Engineers
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• v.16 no.1
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• pp.51-58
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• 1990

A deterministic capacity expansion planning model for a two-capacity type facility is analyzed to determine the sizes to be expanded in each period so as to supply the known demands for two distinct capacity type(product) on time and to minimize the total cost incurred over a finite planning horizon of T periods. The model assumes that capacity unit of the facility simultaneously serves a prespecified number of demand units of each capacity type, that capacity type 1 can be used to supply demands for capacity type 2, but that capacity type 2 can't be used to supply demands for capacity type 1. Capacity expansion and excess capacity holding cost functions considered are nondecreasing and concave. The structure of an optimal solution is characterized and then used in developing an efficient dynamic programming algorithm that finds optimal capacity planning policy.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.32 no.2
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• pp.1-12
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• 2009

Distribution centers in a distribution system that consists of the distribution centers and retailers supplies products to retailers. At the present, although total capacity of the distribution centers are enough to supply total demand of retailers, capacity of the distribution centers need to be expanded to satisfy the demand of retailers in case that future demand of the retailers will be increased. Capacity expansion model in a distribution system is to determine the location and size of expansion distribution centers that minimize costs among given distribution centers. Transportation amount from distribution center to retailers also is determined. The costs factors are the capacity expansion costs of the distribution centers and the transportation costs from the distribution centers to the retailers. A model is formulated, and a genetic algorithm based solution procedure is developed. A numerical example is shown and the algorithm is analyzed through examples.

• New & Renewable Energy
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• v.7 no.2
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• pp.18-27
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• 2011

Management flexibility to adapt its future actions in response to altered future market conditions can expand the value of an investment opportunity by improving its upside potential without the change in the downside losses. Module manufacturers in solar industry continuously have to decide how much and when its production capacity should be expanded with regards to the demand in the global markets. Either over- or under-investment can cause sunk and/or opportunity costs to the module manufacturers. Option of exercising the additional investments only on favorable opportunities can increase total value of the investment. This paper analyzes the case which shows that the expansion of production capacity with more expandibility can have more value than the rigid plan of capacity expansion. The expansion option value is equivalent to KRW 38.286 billion, thus switching the negative NPV of the initial investment opportunity into the positive value. High volatility and the high growth in the cashflows as the major business features of the renewable energy provide condition where real options can play the crucial role in increasing the investment value as well as in determining the size and timing of capacity expansion in the course of capital budgeting process.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 1999.12a
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• pp.21-25
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• 1999

Planning support systems(PSS) add more advanced spatial analysis functions than Geographic information systems(GIS) and intertemporal functions to the functions of spatial decision support systems(SDSS). This paper reports the continuing development of a PSS providing a framework that facilitates urban planners and civil engineers in conducting coherent deliberations about planning, design and operation & maintenance(O&M) of water-distribution networks for urban growth management. The PSS using dynamic optimization model, modeling-to-generate-alternatives, value engineering(VE) and life-cycle cost(LCC) can generate network alternatives in consideration of initial cost and O&H cost. Users can define alternatives by the direct manipulation of networks or by the manipulation of parameters in the models. The water-distribution network analysis model evaluates the performance of the user-defined alternatives. The PSS can be extended to include the functions of generating sewer network alternatives, combining water-distribution and sewer networks, eventually the function of planning, design and O&H of housing sites. Capacity expansion by the dynamic water-distribution network optimization model using MINLP includes three advantages over capacity expansion using optimal control theory(Kim and Hopkins 1996): 1) finds expansion alternatives including future capacity expansion times, sizes, locations, and pipe types of a water-distribution network provided, 2) has the capabilities to do the capacity expansion of each link spatially and intertemporally, and 3) requires less interaction between models. The modeling using MINLP is limited in addressing the relationship between cost, price, and demand, which the optimal control approach can consider. Strictly speaking, the construction and O&M costs of water-distribution networks influence the price charged for the served water, which in turn influence the. This limitation can be justified in rather small area because price per unit water in the area must be same as that of neighboring area, i.e., the price is determined administratively. Planners and engineers can put emphasis on capacity expansion without consideration of the relationship between cost, price, and demand.

• 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.

• Journal of Power System Engineering
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• v.10 no.3
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• pp.81-87
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• 2006

This paper deals with an empirical model for decoupling control to control the refrigeration system effectively. The conventional control schemes of the system are mainly focused on representative two control methods, superheat control and capacity control. The capacity control is basically conducted to respond partial loading conditions on the purpose of energy saving. The superheat control is mainly carried out to maintain maximum coefficient of performance (COP). In the variable speed refrigeration system, the capacity and the superheat are controlled by inverters and electronic expansion valves respectively for saving energy and improving cost performance. The capacity and superheat can not be controlled independently because of interfering loop when the compressor speed and opening angle electronic expansion valve is varied. Therefore, we suggest decoupling model to eliminate the interfering loop at first. Next, each transfer function in decoupling control model is obtained from number of experiments.

• 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.

• Korean Management Science Review
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• v.20 no.1
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• pp.65-76
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• 2003

The increased environmental concerns and the emphasis on recycling are gradually shifting the orientation of municipal solid waste (MSW) management. This paper is designed to evaluate regionalization programs for MSW management system. We developed a mixed intiger network programming (MIP) model to identify environment-friendly, cost-effective expansion plans for regionalization scenarios considered. The MIP model is a dynamic capacity expansion model based on the network flow model that depicts the MSW management cycle. In particular, our model is designed to determine the optimal form of regionalization using binary variables. We apply this model to assess the regionalization program of Seoul Metropolitan City, which includes three scenarios such as 1) districting, 2) regionalization with neighboring self-governing districts, and 3) g1obalization with all districts. We demonstrate how our model can be used to plan the MSW system. The results indicate that optimal regionalization with nearby self-governing districts can eliminate unnecessary landfills and expansions if jurisdictional obstacles are removed.