• Title/Summary/Keyword: Nonconvex optimization

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OPTIMALITY CONDITIONS AND DUALITY RESULTS OF THE NONLINEAR PROGRAMMING PROBLEMS UNDER ρ-(p, r)-INVEXITY ON DIFFERENTIABLE MANIFOLDS

  • Jana, Shreyasi;Nahak, Chandal
    • Journal of applied mathematics & informatics
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    • v.32 no.3_4
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    • pp.491-502
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    • 2014
  • In this paper, by using the notion of ${\rho}$-(p,r)-invexity assumptions on the functions involved, optimality conditions and duality results (Mond-Weir, Wolfe and mixed type) are established on differentiable manifolds. Counterexample is constructed to justify that our investigations are more general than the existing work available in the literature.

An Improved Differential Evolution for Economic Dispatch Problems with Valve-Point Effects (개선된 DE 알고리즘을 이용한 전력계통의 경제급전)

  • Jeong, Yun-Won;Lee, Joo-Won;Jeong, Sang-Yun;Park, Jong-Bae;Shin, Joong-Rin
    • Proceedings of the KIEE Conference
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    • 2007.07a
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    • pp.848-849
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    • 2007
  • This paper presents an efficient approach for solving the economic dispatch (ED) problems with valve-point effects using differential evolution (DE). A DE, one of the evolutionary algorithms (EAs), is a novel optimization method capable of handling nonlinear, non-differentiable, and nonconvex functions. And an efficient constraints treatment method (CTM) is applied to handle the equality and inequality constraints. The resultant DE-CTM algorithm is very effective in solving the ED problems with nonconvex cost functions. To verify the superiority of the proposed method, a sample ED problem with valve-point effects is tested and its results are compared with those of previous works. The simulation results clearly show that the proposed DE-CTM algorithm outperforms other state-of-the-art algorithms in solving ED problems with valve-point effects

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Optimization of Triple Response Systems by Using the Dual Response Approach and the Hooke-Jeeves Search Method

  • Fan, Shu-Kai S.;Huang, Chia-Fen;Chang, Ko-Wei;Chuang, Yu-Chiang
    • Industrial Engineering and Management Systems
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    • v.9 no.1
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    • pp.10-19
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    • 2010
  • This paper presents an extended computing procedure for the global optimization of the triple response system (TRS) where the response functions are nonconvex (nonconcave) quadratics and the input factors satisfy a radial region of interest. The TRS arising from response surface modeling can be approximated using a nonlinear mathematical program involving one primary (objective) function and two secondary (constraints) functions. An optimization algorithm named triple response surface algorithm (TRSALG) is proposed to determine the global optimum for the nondegenerate TRS. In TRSALG, the Lagrange multipliers of target (secondary) functions are computed by using the Hooke-Jeeves search method, and the Lagrange multiplier of the radial constraint is located by using the trust region (TR) method at the same time. To ensure global optimality that can be attained by TRSALG, included is the means for detecting the degenerate case. In the field of numerical optimization, as the family of TR approach always exhibits excellent mathematical properties during optimization steps, thus the proposed algorithm can guarantee the global optimal solution where the optimality conditions are satisfied for the nondegenerate TRS. The computing procedure is illustrated in terms of examples found in the quality literature where the comparison results with a gradient-based method are used to calibrate TRSALG.

Stochastic Optimization Approach for Parallel Expansion of the Existing Water Distribution Systems (추계학적 최적화방법에 의한 기존관수로시스템의 병열관로 확장)

  • Ahn, Tae-Jin;Choi, Gye-Woon;Park, Jung-Eung
    • Water for future
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    • v.28 no.2
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    • pp.169-180
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    • 1995
  • The cost of a looped pipe network is affected by a set of loop flows. The mathematical model for optimizing the looped pipe network is expressed in the optimal set of loop flows to apply to a stochastic optimization method. Because the feasible region of the looped pipe network problem is nonconvex with multiple local optima, the Modified Stochastic Probing Method is suggested to efficiently search the feasible region. The method consists of two phase: i) a global search phase(the stochastic probing method) and ii) a local search phase(the nearest neighbor method). While the global search sequentially improves a local minimum, the local search escapes out of a local minimum trapped in the global search phase and also refines a final solution. In order to test the method, a standard test problem from the literature is considered for the optimal design of the paralled expansion of an existing network. The optimal solutions thus found have significantly smaller costs than the ones reported previously by other researchers.

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Rank-constrained LMI Approach to Simultaneous Linear Quadratic Optimal Control Design (계수조건부 LMI를 이용한 동시안정화 LQ 최적제어기 설계)

  • Kim, Seog-Joo;Cheon, Jong-Min;Kim, Jong-Moon;Kim, Chun-Kyung;Lee, Jong-Moo;Kwon, Soom-Nam
    • Journal of Institute of Control, Robotics and Systems
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    • v.13 no.11
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    • pp.1048-1052
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    • 2007
  • This paper presents a rank-constrained linear matrix inequality(LMI) approach to simultaneous linear-quadratic(LQ) optimal control by static output feedback. Simultaneous LQ optimal control is formulated as an LMI optimization problem with a nonconvex rank condition. An iterative penalty method recently developed is applied to solve this rank-constrained LMI optimization problem. Numerical experiments are performed to illustrate the proposed method, and the results are compared with those of previous work.

Multi-Objective Controller Design using a Rank-Constrained Linear Matrix Inequality Method (계수조건부 LMI를 이용한 다목적 제어기 설계)

  • Kim, Seog-Joo;Kim, Jong-Moon;Cheon, Jong-Min;Kwon, Soon-Mam
    • Journal of Institute of Control, Robotics and Systems
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    • v.15 no.1
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    • pp.67-71
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    • 2009
  • This paper presents a rank-constrained linear matrix inequality (LMI) approach to the design of a multi-objective controller such as $H_2/H_{\infty}$ control. Multi-objective control is formulated as an LMI optimization problem with a nonconvex rank condition, which is imposed on the controller gain matirx not Lyapunov matrices. With this rank-constrained formulation, we can expect to reduce conservatism because we can use separate Lyapunov matrices for different control objectives. An iterative penalty method is applied to solve this rank-constrained LMI optimization problem. Numerical experiments are performed to illustrate the proposed method.

A Weighted Mean Squared Error Approach Based on the Tchebycheff Metric in Multiresponse Optimization (Tchebycheff Metric 기반 가중평균제곱오차 최소화법을 활용한 다중반응표면 최적화)

  • Jeong, In-Jun
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.16 no.1
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    • pp.97-105
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    • 2015
  • Multiresponse optimization (MRO) seeks to find the setting of input variables, which optimizes the multiple responses simultaneously. The approach of weighted mean squared error (WMSE) minimization for MRO imposes a different weight on the squared bias and variance, which are the two components of the mean squared error (MSE). To date, a weighted sum-based method has been proposed for WMSE minimization. On the other hand, this method has a limitation in that it cannot find the most preferred solution located in a nonconvex region in objective function space. This paper proposes a Tchebycheff metric-based method to overcome the limitations of the weighted sum-based method.

Joint Optimization Algorithm Based on DCA for Three-tier Caching in Heterogeneous Cellular Networks

  • Zhang, Jun;Zhu, Qi
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.7
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    • pp.2650-2667
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    • 2021
  • In this paper, we derive the expression of the cache hitting probability with random caching policy and propose the joint optimization algorithm based on difference of convex algorithm (DCA) in the three-tier caching heterogeneous cellular network assisted by macro base stations, helpers and users. Under the constraint of the caching capacity of caching devices, we establish the optimization problem to maximize the cache hitting probability of the network. In order to solve this problem, a convex function is introduced to convert the nonconvex problem to a difference of convex (DC) problem and then we utilize DCA to obtain the optimal caching probability of macro base stations, helpers and users for each content respectively. Simulation results show that when the density of caching devices is relatively low, popular contents should be cached to achieve a good performance. However, when the density of caching devices is relatively high, each content ought to be cached evenly. The algorithm proposed in this paper can achieve the higher cache hitting probability with the same density.

RIS Selection and Energy Efficiency Optimization for Irregular Distributed RIS-assisted Communication Systems

  • Xu Fangmin;Fu Jinzhao;Cao HaiYan;Hu ZhiRui
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.17 no.7
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    • pp.1823-1840
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    • 2023
  • In order to improve spectral efficiency and reduce power consumption for reconfigurable intelligent surface (RIS) assisted wireless communication systems, a joint design considering irregular RIS topology, RIS on-off switch, power allocation and phase adjustment is investigated in this paper. Firstly, a multi-dimensional variable joint optimization problem is established under multiple constraints, such as the minimum data requirement and power constraints, with the goal of maximizing the system energy efficiency. However, the proposed optimization problem is hard to be resolved due to its property of nonlinear nonconvex integer programming. Then, to tackle this issue, the problem is decomposed into four sub-problems: topology design, phase shift adjustment, power allocation and switch selection. In terms of topology design, Tabu search algorithm is introduced to select the components that play the main role. For RIS switch selection, greedy algorithm is used to turn off the RISs that play the secondary role. Finally, an iterative optimization algorithm with high data-rate and low power consumption is proposed. The simulation results show that the performance of the irregular RIS aided system with topology design and RIS selection is better than that of the fixed topology and the fix number of RISs. In addition, the proposed joint optimization algorithm can effectively improve the data rate and energy efficiency by changing the propagation environment.

OPTIMAL DESIGN FOR CAPACITY EXPANSION OF EXISTING WATER SUPPLY SYSTEM

  • Ahn, Tae-Jin;Lyu, Heui-Jeong;Park, Jun-Eung;Yoon, Yong-Nam
    • Water Engineering Research
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    • v.1 no.1
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    • pp.63-74
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    • 2000
  • This paper presents a two- phase search scheme for optimal pipe expansion of expansion of existing water distribution systems. In pipe network problems, link flows affect the total cost of the system because the link flows are not uniquely determined for various pipe diameters. The two-phase search scheme based on stochastic optimization scheme is suggested to determine the optimal link flows which make the optimal design of existing pipe network. A sample pipe network is employed to test the proposed method. Once the best tree network is obtained, the link flows are perturbed to find a near global optimum over the whole feasible region. It should be noted that in the perturbation stage the loop flows obtained form the sample existing network are employed as the initial loop flows of the proposed method. It has been also found that the relationship of cost-hydraulic gradient for pipe expansion of existing network affects the total cost of the sample network. The results show that the proposed method can yield a lower cost design than the conventional design method and that the proposed method can be efficiently used to design the pipe expansion of existing water distribution systems.

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