• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.1C
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• pp.90-97
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• 2009

The advantages of the orthogonal frequency division multiplexing (OFDM) are high spectral efficiency, resiliency to RF interference, and lower multi-path distortion. To further utilize vast channel capacity of the multiuser OFDM, one has to find the efficient adaptive subchannel and bit allocation among users. In this paper, we propose an 0-1 integer programming model formulating the optimal subchannel and bit allocation problem of the multiuser OFDM. We employ a dual-decomposition method that provides a tight linear programming (LP) relaxation bound. Simulation results are provided to show the effectiveness of the 0-1 integer programming model. MATLAB simulation on a system employing M-ary quardarature amplitude modulation (MQAM) assuming a frequency-selective channel consisting of three independent Rayleigh multi-paths are carried with the optimal subchannel and bit allocation solution generated by 0-1 integer programming model.

• Journal of Korean Institute of Industrial Engineers
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• v.32 no.2
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• pp.74-81
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• 2006

In this paper, we deal with the separation of data by concurrently determined, piecewise nonlinear discriminant functions. Toward the end, we develop a new $l_1$-distance norm error metric and cast the problem as a mixed 0-1 integer and linear programming (MILP) model. Given a finite number of discriminant functions as an input, the proposed model considers the synergy as well as the individual role of the functions involved and implements a simplest nonlinear decision surface that best separates the data on hand. Hence, exploiting powerful MILP solvers, the model efficiently analyzes any given data set for its piecewise nonlinear separability. The classification of four sets of artificial data demonstrates the aforementioned strength of the proposed model. Classification results on five machine learning benchmark databases prove that the data separation via the proposed MILP model is an effective supervised learning methodology that compares quite favorably to well-established learning methodologies.

• Journal of Communications and Networks
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• v.17 no.5
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• pp.473-481
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• 2015

In this study, we propose a clustering algorithm to enhance the performance of wireless sensor and actuator networks (WSANs). In each cluster, a multi-level hierarchical structure can be applied to reduce energy consumption. In addition to the cluster head, some nodes can be selected as intermediate nodes (INs). Each IN manages a subcluster that includes its neighbors. INs aggregate data from members in its subcluster, then send them to the cluster head. The selection of intermediate nodes aiming to optimize energy consumption can be considered high computational complexity mixed-integer linear programming. Therefore, a heuristic lowest energy path searching algorithm is proposed to reduce computational time. Moreover, a channel assignment scheme for subclusters is proposed to minimize interference between neighboring subclusters, thereby increasing aggregated throughput. Simulation results confirm that the proposed scheme can prolong network lifetime in WSANs.

• Journal of Communications and Networks
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• v.13 no.6
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• pp.612-620
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• 2011

Recently, one of the problems with the Internet is the issue of scalability. To this end, locator/identifier separation protocol (LISP), which separates end-system identifiers and routing locators, has been proposed as a solution. In the LISP deployed network, the ingress and egress nodes of inter-AS traffic is determined by edge router selection (ERS) and endpoint identifier-routing locator mapping assignment (ERMA). In this paper, joint optimizations of ERS and ERMA for stub networks with and without predetermined link weights are studied and the mixed integer linear programming (MILP) formulations for the problems are given. To make the problem with optimizable link weights tractable, a revised local search algorithm is also proposed. Simulation results show that joint optimization of ERS and ERMA enables better network performance.

• ETRI Journal
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• v.28 no.5
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• pp.631-637
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• 2006

In this paper we study the optimization issues of ring networks employing novel parallel multi-granularity hierarchical optical add-drop multiplexers (OADMs). In particular, we attempt to minimize the number of control elements for the off-line case. We present an integer linear programming formulation to obtain the lower bound in optimization, and propose an efficient heuristic algorithm called global bandwidth resource assignment that is suitable for the design of large-scale OADM networks.

• Journal of the Korea Institute of Military Science and Technology
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• v.23 no.4
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• pp.426-434
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• 2020

This paper studies the impact of the maintenance time of anti-ship missile Harpoon on operational availability with real field data. The Harpoon maintenance simulation model is developed as a testbed for identifying the optimal inventory levels on operational availability. Using multiple linear regression analysis and integer programming, the optimal inventory levels of essential assemblies are suggested. Finally, the result of sensitivity analysis shows the quantitative impact of maintenance time on operational availability and inventory costs. The authors believe that this quantitative analysis can support policy decisions to decrease maintenance time of missiles.

• Journal of the Institute of Convergence Signal Processing
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• v.3 no.1
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• pp.87-92
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• 2002

Placement is an important step in the physical design of VLSI circuits. It is the problem of placing a set of circuit modules on a chip to optimize the circuit performance. The most popular algorithms for placement include the cluster growth, simulated annealing and integer linear programming. In this paper we propose a stochastic evolution algorithm searching solution space for the placement problem, and then compare it with simulated annealing by analyzing the results of each implementation.

• Journal of the Korea Society of Computer and Information
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• v.7 no.3
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• pp.42-48
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• 2002

Placement is an important step in the physical design of VLSI circuits. It is the problem of placing a set of circuit modules on a chip to optimize the circuit performance. The most popular algorithms for placement include the cluster growth, simulated annealing and integer linear programming. In this paper we propose a genetic algorithm searching solution space for the placement problem, and then compare it with simulated annealing by analyzing the results of each implementation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.2
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• pp.478-493
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• 2024

In this paper, the Mixed Integer Linear Programming (MILP) model is improved for searching differential characteristics of block cipher Midori-64, and 4 search strategies of differential path are given. By using strategy IV, set 1 S-box on the top of the distinguisher to be active, and set 3 S-boxes at the bottom to be active and the difference to be the same, then we obtain a 5-round differential characteristics. Based on the distinguisher, we attack 12-round Midori-64 with data and time complexities of 2⁶³ and 2^103.83, respectively. To our best knowledge, these results are superior to current ones.

• Journal of the Korean Operations Research and Management Science Society
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• v.3 no.2
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• pp.95-108
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• 1978

This paper discusses an application of mathematical programming techniques in the paper industry in determining optimal parent roll widths. Parent rolls are made from the reels produced at wide paper machines by slitting them to more manageable widths. The problem is finding a set of the slitting patterns that will minimize the trim loss involved in the sheeting operation. Two programming models, one linear and one mixed integer linear, are presented in this paper. Also presented are the computational experience, the model sensitivity, and the comparison of the optimal solutions with the simulated operational data.