• ETRI Journal
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• 제36권3호
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• pp.506-509
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• 2014

This paper studies the energy efficiency power allocation for cognitive radio networks based on uplink orthogonal frequency-division multiplexing. The power allocation problem is intended to minimize the maximum energy efficiency measured by "Joule per bit" metric, under total power constraint and robust aggregate mutual interference power constraint. However, the above problem is non-convex. To make it solvable, an equivalent convex optimization problem is derived that can be solved by general fractional programming. Then, a robust energy efficiency power allocation scheme is presented. Simulation results corroborate the effectiveness of the proposed methods.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2004년도 춘계학술대회 학술발표 논문집 제14권 제1호
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• pp.523-527
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• 2004

This paper presents a new design methods of the short-term load forecasting system (STLFS) using the data mining. The proposed predictor takes form of the convex combination of the linear time series predictors for each inputs. The problem of estimating the consequent parameters is formulated by the convex optimization problem, which is to minimize the norm distance between the real load and the output of the linear time series estimator, The problem of estimating the premise parameters is to find the parameter value minimizing the error between the real load and the overall output. Finally, to show the feasibility of the proposed method, this paper provides the short-term load forecasting example.

• Journal of Communications and Networks
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• 제18권6호
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• pp.873-883
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• 2016

In this paper, we focus on maximizing weighted sum energy efficiency (EE) for a multi-cell multi-user channel. In order to solve this non-convex problem, we first decompose the original problem into a sequence of parallel subproblems which can optimized separately. For each subproblem, a base station employs dirty paper coding to maximize the EE for users within a cell while regulating interference induced to other cells. Since each subproblem can be transformed to a convex multiple-access channel problem, the proposed method provides a closed-form solution for power allocation. Then, based on the derived optimal covariance matrix for each subproblem, a local optimal solution is obtained to maximize the sum EE. Finally, simulation results show that our algorithm based on non-linear precoding achieves about 20 percent performance gains over the conventional linear precoding method.

• 제어로봇시스템학회논문지
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• 제11권4호
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• pp.279-283
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• 2005

This paper deals with the design of a low-order H/sub ∞/ controller by using an iterative linear matrix inequality (LMI) method. The low-order H/sub ∞/ controller is represented in terms of LMIs with a rank condition. To solve the non-convex rank-constrained LMI problem, the recently developed penalty function method is applied. With an increasing sequence of the penalty parameter, the solution of the penalized optimization problem moves towards the feasible region of the original non-convex problem. Numerical experiments showed the effectiveness of the proposed algorithm.

• Wind and Structures
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• 제32권4호
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• pp.355-369
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• 2021

Shape optimization of tall buildings is an efficient approach to mitigate wind-induced effects. Several studies have demonstrated the potential of shape modifications to improve the building's aerodynamic properties. On the other hand, it is well-known that the cross-section geometry has a direct impact in the floor area availability and subsequently in the building's profitability. Hence, it is of interest for the designers to find the balance between these two design criteria that may require contradictory design strategies. This study proposes a surrogate-based multi-objective optimization framework to tackle this design problem. Closed-form equations provided by the Eurocode are used to obtain the wind-induced responses for several wind directions, seeking to develop an industry-oriented approach. CFD-based surrogates emulate the aerodynamic response of the building cross-section, using as input parameters the cross-section geometry and the wind angle of attack. The definition of the building's modified plan shapes is done adopting the reduced basis approach, advancing the current strategies currently adopted in aerodynamic optimization of civil engineering structures. The multi-objective optimization problem is solved with both the classical weighted Sum Method and the Weighted Min-Max approach, which enables obtaining the complete Pareto front in both convex and non-convex regions. Two application examples are presented in this study to demonstrate the feasibility of the proposed strategy, which permits the identification of Pareto optima from which the designer can choose the most adequate design balancing profitability and occupant comfort.

• 산업경영시스템학회지
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• 제15권26호
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• pp.67-76
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• 1992

변수의 어떤 값들에 대해 도함수를 가질 수 없는 함수를 최적화해야 하는 등. OR 에서는 여러 상황이 존재한다. 이것은 Convex Analysis〔12〕서 이론적인 differential calculus를 근저로 하는 Non-differentiable Optimization 또는 Non-smooth Optimization 을 취급하는 것이 된다. 이러한 종류의 미분이 가능하지 않은 최적화문제는 연속함수를 위한 종래의 최적화법으로는 그 해법자체가 갖고 있는 연속성의 한계를 극복할 수 없다. 따라서, 이러한 문제를 해결하기 위해 Demyanov〔4〕가 제시한 quasi-differental function의 정의와 이들 함수에 따른 몇가지 주요정리들을 언급하고, 그것들을 토대로 Non-differentiable optimization problem의 수치적인 방법을 수행하기 위해 일종의 modified gradient 법을 제시한다. 이를 이용해서 numerical experiment를 위한 방법을 구체화하여, unrestricted non-differentable optimization problem에 적응하여, 그 수치해 결과를 보여서 그 타당성음 검토하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권1호
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• pp.216-239
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• 2021

The present work addresses the challenging problem of coordinating power allocation with interference management in multi-robot networks by applying the promising expansion capabilities of multiple-input multiple-output (MIMO) and full duplex systems, which achieves it for maximizing the throughput of networks under the impacts of Doppler frequency shifts and external jamming. The proposed power allocation with interference coordination formulation accounts for three types of the interference, including cross-tier, co-tier, and mixed-tier interference signals with cluster head nodes operating in different full-duplex modes, and their signal-to-noise-ratios are respectively derived under the impacts of Doppler frequency shifts and external jamming. In addition, various optimization algorithms, including two centralized iterative optimization algorithms and three decentralized optimization algorithms, are applied for solving the complex and non-convex combinatorial optimization problem associated with the power allocation and interference coordination. Simulation results demonstrate that the overall network throughput increases gradually to some degree with increasing numbers of MIMO antennas. In addition, increasing the number of clusters to a certain extent increases the overall network throughput, although internal interference becomes a severe problem for further increases in the number of clusters. Accordingly, applications of multi-robot networks require that a balance should be preserved between robot deployment density and communication capacity.

• 충청수학회지
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• 제33권2호
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• pp.293-300
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• 2020

In this paper we study an optimal consumption, investment and retirement time choice problem of an investor who receives labor income before her voluntary retirement. And we assume that there is a negative wealth constraint which is a general version of borrowing constraint. Using convex-duality method, we provide the closed-form solutions of the optimization problem.

• 제어로봇시스템학회논문지
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• 제13권10호
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• pp.1000-1006
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• 2007

This paper presents an LMI-based method to design a saturated state-feedback $H_2$ controller for uncertain systems with actuator saturation. Specifically, the paper proposes a sufficient condition such that the system under norm-bounded uncertainties and actuator saturation is asymptotically stable and the $H_2$-norm of the system has an upper-bound. The resulting condition is further utilized to solve a convex optimization problem specified in the context of $H_2$-norm minimization, whose solution yields a saturated $H_2$ controller. A numerical example is presented to show the effectiveness of the proposed method.

• 대한산업공학회지
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• 제26권2호
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• pp.117-127
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• 2000

In this paper, we propose a new convex combination weight rule for the cross decomposition method which is known to be one of the most reliable and promising strategies for the large scale optimization problems. It is called generalized cross decomposition, a modification of linear mean value cross decomposition for specially structured linear programming problems. This scheme puts more weights on the recent subproblem solutions other than the average. With this strategy, we are having more room for selecting convex combination weights depending on the problem structure and the convergence behavior, and then, we may choose a rule for either faster convergence for getting quick bounds or more accurate solution. Also, we can improve the slow end-tail behavior by using some combined rules. Also, we provide some computational test results that show the superiority of this strategy to the mean value cross decomposition in computational time and the quality of bounds.