• Management Science and Financial Engineering
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• v.14 no.2
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• pp.25-44
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• 2008

This paper concentrates on reduction of a Quadratic Fractional Integer Programming Problem (QFIP) to a 0-1 Mixed Linear Programming Problem (0-1 MLP). The solution technique is based on converting the integer variables to binary variables and then the resulting Quadratic Fractional 0-1 Programming Problem is linearized to a 0-1 Mixed Linear Programming problem. It is illustrated with the help of a numerical example and is solved using the LINDO software.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.11
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• pp.166-174
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• 2016

In this paper, we developed a mixed-integer linear programming model for transportation planning of athletes in sports events. The transportation planning of athletes involves finding the lowest-cost and fastest-time plan for distributing athletes from multiple accommodation to stadium. The decision variables associate with the number of driving events, and the total transportation cost is the objective function that needs to be minimized. The proposed method uses mixed integer linear programming to solve transportation problem, thus the global optimality is guaranteed. In order to verify the effectiveness of proposed method, we performed simulation and built the sports event management service platform (SEMSP) for transportation planning.

• Journal of Korea Water Resources Association
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• v.32 no.5
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• pp.525-535
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• 1999

An optimal unit commitment model for efficient management of water and energy resources in a basin using combined mixed integer programming is developed. The combined mixed integer programming model is able to solve the inconsistency problem that may occur from mixed integer programming models. The technique which enables the use of conditional constraints and either-or constraints in the linear programming is also suggested. As a result of applying the combined mixed integer programming model to Lower Colorado River Basin in United States. the basin efficiency is decreased by 1.53% from the results of the mixed integer programming, while it is increased by 0.67% from the results of the historical operation. It is found that the decreased allowable error between power supplies and demands in the combined mixed integer programming causes the decreased basin efficiency.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.1
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• pp.166-173
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• 2013

As the number of IPs and the communication volume among them have constantly increased, on-chip crossbar network is now the most widely-used on-chip communication backbone of contemporary SoCs. The on-chip crossbar network consists of multiple crossbars and the connections among the IPs and the crossbars. As the complexity of SoCs increases, it has also become more and more complex to determine the topology of the crossbar network. To tackle this problem, this paper proposes an on-chip crossbar network topology method for application-specific systems. The proposed method uses mixed integer linear programming to solve the topology synthesis problem, thus the global optimality is guaranteed. Unlike the previous MILP-based methods which represent the topology with adjacency matrixes of IPs and crossbar switches, the proposed method uses the communication edges among IPs as the basic element of the representation. The experimental results show that the proposed MILP formulation outperforms the previous one by improving the synthesis speed by 77.1 times on average, for 4 realistic benchmarks.

• Korean Management Science Review
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• v.25 no.1
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• pp.43-53
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• 2008

This paper considers a profit-based unit commitment problem with fuel consumption constraint and maintenance cost, which is one of the key decision problems in electricity industry. The nature of non-linearity inherent in the constraints and objective functions makes the problem intractable which have led many researches to focus on Lagrangian based heuristics. To solve the problem more effectively, we propose mixed integer programming based solution algorithm linearizing the complex non-linear constraints and objectives functions. The computational experiments using the real-world operation data taken from a domestic electricity power generator show that the proposed algorithm solves the given problem effectively.

• Journal of applied mathematics & informatics
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• v.20 no.1_2
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• pp.293-303
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• 2006

This paper describes a numerical scheme for optimal control of a time-dependent linear system to a moving final state. Discretization of the corresponding differential equations gives rise to a linear algebraic system. Defining some binary variables, we approximate the original problem by a mixed integer linear programming (MILP) problem. Numerical examples show that the resulting method is highly efficient.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.4
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• pp.717-725
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• 2011

In the power system with an electric storage system that can increase utilization rate of the source of such new renewable energy, this paper introduces the approach on the daily unit commitment scheduling that determines simultaneously optimum operational condition and output of thermal generators and electric storage device. The unit commitment is one of the most important issues in economic operation and security of short-term operational plan of the power system. It is to determine on/off status of generator to minimize operational cost during the given period. The committed generator should satisfy various operational limitation such as estimated demand by system, spinning reserve condition within minimum operational cost. In order to determine on/off or charge/discharge/idle condition and output level of units and electric storage system, the MILP(Mixed Integer Linear Programming) is suggested. The proposed approach is the mixed method between LP(Linear Programming) and IP(integer programming) which seeks the value of real number and integer that maximize or minimize function objective within given condition. The daily unit commitment problem with the electric storage system is applied to MILP algorithm through linearization and formulation process. The proposed approach is applied to the test system.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.47 no.11
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• pp.787-794
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• 2019

In this paper, a Mixed Integer Linear Programming(MILP) approach for solving optimal Weapon-Target Assignment(WTA) problem of multiple dissimilar Closed-In Weapon Systems (CIWS) is proposed. Generally, WTA problems are formulated in nonlinear mixed integer optimization form, which often requires impractical exhaustive search to optimize. However, transforming the problem into a structured MILP problem enables global optimization with an acceptable computational load. The problem of interest considers defense against several threats approaching the asset from various directions, with different time of arrival. Moreover, we consider multiple dissimilar CIWSs defending the asset. We derive a MILP form of the given nonlinear WTA problem. The formulated MILP problem is implemented with a commercial optimizer, and the optimization result is proposed.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.4
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• pp.212-221
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• 2022

Currently, issues related to freight at Vietnamese logistics companies are becoming more and more urgent because of typical problems in Vietnam such as traffic, infrastructure, and application of information technology. This problem has been studied by applying many different approaches such as Integer Programming (LP), Mixed Integer Programming (MIP), hybrid, meta search, … In this paper, we applied the ILP model in order to deal with the VRP problem in a small size logistics company which is very popular in Vietnam. The experiments showed promising results with some optimal solutions with some small extra costs.

• Journal of the Korean Society of Safety
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• v.14 no.2
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• pp.70-76
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• 1999

In this paper, a mixed-integer programming approach is presented for adjusting the voltage profiles in a power system. The advent of large-scaled system makes the reactive power and voltage problem-an attempt to achieve an overall improvement of system security, service quality and economy-more complex and seriously, Although the problem is originally a nonlinear optimization problem, it can be formulated as a mixed integer linear programming(MILP) problem without deteriorating of solution accuracy to a certain extent. The MILP code is developed by the branch and bound process search for the optimal solution. The variable for modeling transformer tap positions is handled as discrete one, and other variables continuous ones. Numerical data resulting from case study using a modified IEEE 30 bus system with outaged line show that the MILP can produce more reductions of magnitude in the operating cost. The convergence characteristics of the results are also presented and discussed.