• Journal of Information Processing Systems
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• 제17권2호
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• pp.426-439
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• 2021

To alleviate the cold-start problem and data sparsity in web service recommendation and meet the personalized needs of users, this paper proposes a personalized web service recommendation method based on a hybrid social network and multi-objective immune optimization. The network adds the element of the service provider, which can provide more real information and help alleviate the cold-start problem. Then, according to the proposed service recommendation framework, multi-objective immune optimization is used to fuse multiple attributes and provide personalized web services for users without adjusting any weight coefficients. Experiments were conducted on real data sets, and the results show that the proposed method has high accuracy and a low recall rate, which is helpful to improving personalized recommendation.

• 산업공학
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• 제20권4호
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• pp.458-468
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• 2007

Artificial immune systems (AIS) are one of natural computing inspired by the natural immune system. The fault detection, the pattern recognition, the system control and the optimization are major application area of artificial immune systems. This paper gives a concept of artificial immune systems and useful techniques as like the clonal selection, the immune network theory and the negative selection. A concise survey on the optimization problem based on artificial immune systems is generated. The overall performance of artificial immune systems for the optimization problem is discussed.

• 설비공학논문집
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• 제18권8호
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• pp.635-640
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• 2006

An optimizer has been applied for the optimal design of pipe diameters in the pipe flow network problems. Pipe network flow analysis, which is developed separately, is performed within the interface for the optimization algorithm. A pipe network is chosen for the test, and optimizer GenOpt is applied with Holder-Mead-O'Niell's simplex algorithm after solving the network flow problem by the Newton-Raphson method. As a result, optimally do-signed pipe diameters are successfully obtained which minimize the total design cost. Design cost of pipe flow network can be considered as the sum of pipe installation cost and pump operation cost. In this study, a practical and efficient solution method for the pipe network optimization is presented. Test system is solved for the demonstration of the present optimization technique.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2017년도 춘계학술대회
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• pp.649-651
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• 2017

클러스터링 문제는 무선 애드 혹 네트워크의 네트워크 수명과 확장성을 향상시키는 문제 중 하나이다. 이 문제는 무선 애드 혹 네트워크의 설계 및 운영과 관련된 어려운 조합 최적화 문제이다. 본 논문에서는 네트워크 수명을 최대화하고 무선 애드 혹 네트워크의 확장성을 고려한 효율적인 클러스터링 알고리즘을 제안한다. 클러스터링 문제는 NP-hard 문제로 알려져 있습니다. 따라서 본 논문에서는 노드의 수가 많은 네트워크에서 합리적인 시간 내에 최적의 해를 효율적으로 얻을 수 있는 최적화 방식을 사용하여 문제를 해결한다. 제안된 알고리즘은 노드의 전력과 클러스터링 비용을 고려하여 클러스터 헤드를 선택하고 클러스터를 구성한다. 우리는 노드의 전송에너지 측면에서 시뮬레이션을 통해 성능을 평가한다. 시뮬레이션 결과는 제안된 알고리즘이 기존의 알고리즘보다 성능이 우수함을 보여 준다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권6호
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• pp.2282-2303
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• 2021

To solve the problems of heavy computing load and system transmission pressure in energy internet (EI), we establish a three-tier cloud-edge integrated EI network based on a cloud-edge collaborative computing to achieve the tradeoff between energy consumption and the system delay. A joint optimization problem for resource allocation and task offloading in the threetier cloud-edge integrated EI network is formulated to minimize the total system cost under the constraints of the task scheduling binary variables of each sensor node, the maximum uplink transmit power of each sensor node, the limited computation capability of the sensor node and the maximum computation resource of each edge server, which is a Mixed Integer Non-linear Programming (MINLP) problem. To solve the problem, we propose a joint task offloading and resource allocation algorithm (JTOARA), which is decomposed into three subproblems including the uplink transmission power allocation sub-problem, the computation resource allocation sub-problem, and the offloading scheme selection subproblem. Then, the power allocation of each sensor node is achieved by bisection search algorithm, which has a fast convergence. While the computation resource allocation is derived by line optimization method and convex optimization theory. Finally, to achieve the optimal task offloading, we propose a cloud-edge collaborative computation offloading schemes based on game theory and prove the existence of Nash Equilibrium. The simulation results demonstrate that our proposed algorithm can improve output performance as comparing with the conventional algorithms, and its performance is close to the that of the enumerative algorithm.

• 경영과학
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• 제24권2호
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• pp.127-142
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• 2007

This study deals with the optimal design of mobile access network connecting base stations(BSs) and mobile switching centers(MSCs). Generally mobile operators constitute their access networks by leasing communication lines. Using the characteristic of leased line rate based on administration region, we build an optimization model for mobile access network design which has much smaller number of variables than the existing researches. And we develop a GUI based optimization tool integrating the well-known softwares such as MS EXCEL. MS VisualBasic, MS PowerPoint and Ip_solve, a freeware optimization software. Employing the current access network configuration of a Korean mobile carrier, this study using the optimization tool obtain an optimal solution for both single MSC access network and nation-wide access network. Each optimal access network achieves 7.45% and 9.49% save of lease rate, respectively. Considering the monthly charge and total amount of lease line rate, our optimization tool provides big amount of save in network operation cost. Besides the graphical representation of access networks makes the operator easily understand and compare current and optimal access networks.

• 한국통신학회논문지
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• 제32권10A호
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• pp.1023-1033
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• 2007

This study considers a joint congestion control, routing and power control for energy-constrained wireless networks. A mathematical model is introduced which includes maximization of network utility, maximization of network lifetime, and trade-off between network utility and network lifetime. The framework would maximize the overall throughput of the network where the overall throughput depends on the data flow rates which in turn is dependent on the link capacities. The link capacity on the other hand is a function of transmit power levels and link Signal-to-Interference-plus-Noise-Ratio (SINR) which makes the power allocation problem inherently difficult to solve. Using dual decomposition techniques, subgradient method, and logarithmic transformations, a joint algorithm for rate and power allocation problems was formulated. Numerical examples for each optimization problem were also provided.

• 대한산업공학회지
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• 제35권1호
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• pp.87-91
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• 2009

In the server disconnection problem, a network with m servers and their users is given and an attacker is to destroy a set of edges to maximize his net gain defined as the total disconnected utilities of the users minus the total edge-destruction cost. The problem is known to be NP-hard. In this paper, we study the server disconnection problem restricted to a ring network. We present an efficient combinatorial algorithm that generates an optimal solution in polynomial time.

• 대한전기학회논문지
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• 제38권8호
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• pp.585-592
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• 1989

This paper presents an efficient algorithm for the reactive planning of transmission network under normal operating conditions. The optimal operation of a power system is a prerequisite to obtain the optimal investment planning. The operation problem is decomposed into a P-optimization module and a Q-optimization module, but both modules use the same objective function of generation cost. In the investment problem, a new variable decomposition technique is adopted which can operate the operation and the investment variables. The optimization problem is solved by using the gradient projection method (GPM).

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권2호
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• pp.565-581
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• 2019

This paper investigates the wireless powered two way relay network (WPTWRN), where two single-antenna users and one single-antenna relay firstly harvest energy from signals emitted by a multi-antenna power beacon (PB) and then two users exchange information with the help of the relay by using their harvested energies. In order to improve the energy transfer efficiency, energy beamforming at the PB is deployed. For such a network, to explore the performance limit of the presented WPTWRN, an optimization problem is formulated to obtain the achievable rate region bounds by jointly optimizing the time allocation and energy beamforming design. As the optimization problem is non-convex, it is first transformed to be a convex problem by using variable substitutions and semidefinite relaxation (SDR) and then solve it efficiently. It is proved that the proposed method achieves the global optimum. Simulation results show that the achievable rate region of the presented WPTWRN architecture outperforms that of wireless powered one way relay network architecture. Results also show that the relay location has significant impact on achievable rate region of the WPTWRN.