• Journal of the Korean Operations Research and Management Science Society
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• v.41 no.3
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• pp.23-36
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• 2016

We consider a model that minimizes the total cost incurred by assigning available weapons to existing targets in order to reduce enemy threats, which is called the weapon target assignment problem (WTAP). This study addresses the stochastic versions of WTAP, in which data, such as the probability of destroying a target, are given randomly (i.e., data are identified with certain probability distributions). For each type of random data or parameter, we provide a stochastic optimization model on the basis of the expected value or scenario enumeration. In particular, when the probabilities of destroying targets depending on weapons are stochastic, we present a stochastic programming formulation with a simple recourse. We show that the stochastic model can be transformed into a deterministic equivalent mixed integer programming model under a certain discrete probability distribution of randomness. We solve the stochastic model to obtain an optimal solution via the mixed integer programming model and compare this solution with that of the deterministic model.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.392-392
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• 2000

This study performs optimization of paper mill scheduling using MINLP(Mixed-Integer Non-Linear Programming) method and 2-step decomposing strategy. Paper mill process is normally composed of five units: paper machine, coater, rewinder, sheet cutter and roll wrapper/ream wrapper. Various kinds of papers are produced through these units. The bottleneck of this process is how to cut product papers efficiently from raw paper reel and this is called trim loss problem or cutting stock problem. As the trim must be burned or recycled through energy consumption, minimizing quantity of the trim is important. To minimize it, the trim loss problem is mathematically formulated in MINLP form of minimizing cutting patterns and trim as well as satisfying customer's elder. The MINLP form of the problem includes bilinearity causing non-linearity and non-convexity. Bilinearity is eliminated by parameterization of one variable and the MINLP form is decomposed to MILP(Mixed-Integer Linear programming) form. And the MILP problem is optimized by means of the optimization package. Thus trim loss problem is efficiently minimized by this 2-step optimization method.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.68 no.4
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• pp.513-522
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• 2019

We calculate the benefit of distributed combined heat power generators from avoiding a transmission expansion cost by building distributed generators near electricity demand centers. We determine a transmission expansion plan by solving a mixed integer linear problem, where we modify capacities of existing transmission lines and build new transmission lines. We calculate the benefit by comparing the sum of generation and transmission expansion costs with or without distributed generators through two simulation frames. In the first frame, for the current demand, we substitute existing distributed generators for non-distributed generators and measure an additional cost to balance the generation and demand. In the second frame, for increased future demand, we compare the cost to invest only in distributed generators to the cost to invest only in non-distributed generators. As a result, we show that the distributed generators have at least 5.8 won/kWh of the benefit from avoiding the transmission expansion cost.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2023.05a
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• pp.223-224
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• 2023

Optimal fleet management in the planning stage is one of the most critical activities that guarantee successful construction projects. In South Korea, the construction standard production rate database (CSPRD) is normally employed. However, when it comes to a trade-off problem that involves decision-making on optimal sets of equipment to perform a certain task, the method will require the planners' in-depth knowledge and experience regarding the target process and a time consuming estimation of the performance of every possible scenario must be conducted for the deduction of the optimal fleet management. On this account, this research paper proposes a lightweight method of using mixed integer nonlinear programming (MINLP) in multi-objective problems based on CSPRD-based mathematical equations to assist planners in the preplanning stage of choosing the optimal sets of types and size machinery to efficiently arrange the construction scheduling and budgeting.

• Korea Trade Review
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• v.46 no.2
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• pp.213-228
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• 2021

In recent year, US government requires local investment ,unlike in the past, when import restrictions and tariff were imposed. In this situation, many companies are considering new investment in the US and entering the local market. However, research on the optimal investment plan along with the case analysis on trade regulation is extremely limited and more research needs to be conducted. Accordingly, this study aims to suggest the implications and countermeasure of the SCM and logistical perspective by studying the optimal measures for the new investment of each company due to trade regulation. As a research method, the gravity location model, Mixed Integer Linear Programming Model were used to select the optimal automobile manufacturing factory considering each state's population. This study will be implication of SCM and logistics perspective not only for companies considering new investment in the US but also for the government to conduct trade negotiations. In the future, it is expected that the US trade pressure will increase and affect Korea in many ways. Therefore, in order to cope with such difficult situation in a timely manner, continuous research considering various possibilities is needed in the future.

• Journal of Intelligence and Information Systems
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• v.9 no.1
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• pp.71-89
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• 2003

Although many studies demonstrate that one technique outperforms the others for a given data set, there is often no way to tell a priori which of these techniques will be most effective in the classification problems. Alternatively, it has been suggested that a better approach to classification problem might be to integrate several different forecasting techniques. This study proposes the linearly combining methodology of different classification techniques. The methodology is developed to find the optimal combining weight and compute the weighted-average of different techniques' outputs. The proposed methodology is represented as the form of mixed integer programming. The objective function of proposed combining methodology is to minimize total misclassification cost which is the weighted-sum of two types of misclassification. To simplify the problem solving process, cutoff value is fixed and threshold function is removed. The form of mixed integer programming is solved with the branch and bound methods. The result showed that proposed methodology classified more accurately than any of techniques individually did. It is confirmed that Proposed methodology Predicts significantly better than individual techniques and the other combining methods.

• IE interfaces
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• v.7 no.2
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• pp.75-85
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• 1994

This paper presents a production scheduling model in a block assembly shop in shipbuilding industry. In a block assembly shop, the most important performance criterion is load leveling, which balances manpower and work area utilization through the planning horizon. The problem is formulated as a mixed-integer nonlinear programming(MINLP) problem of which objective function is to optimize load leveling. The developed MINLP problem can not be solvable due to computational complexity. The MINLP problem is decomposed into two stage mixed-integer linear programming (MILP) problems to obtain a good solution, but the decomposed MILP problems are still computationally intractable because of combinatorial complexity. Therfore, a heuristic method using linear programming is proposed to solve two stage MILP problems sequentially. The proposed heuristic generates a good production schedule within a reasonable computation time, and it is easily applicable for establishing the production schedule in a block assembly shop in shipbuilding industry.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.23 no.61
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• pp.41-50
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• 2000

Cell formation(CF) Is to group parts with similar geometry, function, material and process into part families, and the corresponding machines into machine cells. Cell formation solutions often contain exceptional elements(EEs). Also, the following objective functions - minimizing the total costs of dealing with exceptional elements and maximizing total similarity coefficients between parts - have been used in CF modeling. Thus, multiobjective programming approach can be developed to model cell formation problems with two conflicting objective functions. This paper presents an effective cell formation method with fuzzy multiobjective nonlinear mixed-integer programming simultaneously to form machine cells and to minimize the cost of eliminating EEs.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.34 no.3
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• pp.97-105
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• 2011

Previous researches have focused on the efficiency of project execution and the satisfaction of internal customers In view of the fact that a project is successful if any defects are not found in the short-term performance test of the project final outcome. To execute a project that both internal customer and external customer are satisfied in terms of longer-term benefit perspective, the project claim costs (PCC) which may occur for the warranty period of the project final outcome should be considered. We propose a model included PCC to the linear programming between time and cost to expedite a project and perform the validity test by applying the model to an example project. This model and related procedure will contribute to overall project activities' cost reduction by taking preventive actions for PCC.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.6
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• pp.714-723
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• 1999

This paper presents a short-term scheduling algorithm for the operation of steelmaking processes. The scope of the problem covers refining of the hot iron transferred form a blast furnace, ladle treatment, continuous casting, hot-rolling, and coiling for the final products that should satisfy the given demand. The processing time at each unit depends on how much the batch amount is treated, and te dedicated intermediate storage with finite capacity between the units is considered. Resource constraints and initial amount of each state are incorporated into the presented scheduling model for the algorithm of on-line scheduling. We propose amixed integer linear programming (MILP) model with two objectives for the scheduling. The first is to maximize the total profit while atisfying the due date constraint for each product. And the second is to minimize the total processing time, makespan, while satisfying the demand for each product. Especially, we observe the effect of penalizing the intermediate storage and the inventory level of the final product on the scheduling results.