• Title/Summary/Keyword: Multiple Optimization Problem

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Joint TAS and Power Allocation for IHDAF Relaying M2M Cooperative Networks

  • Xu, Lingwei;Zhang, Hao;Gulliver, T. Aaron
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.10 no.5
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    • pp.1957-1975
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    • 2016
  • The outage probability (OP) performance of multiple-relay-based incremental hybrid decode-amplify-forward (IHDAF) relaying mobile-to-mobile (M2M) networks with transmit antenna selection (TAS) over N-Nakagami fading channels is investigated in this paper. The closed-form expressions for approximate OP of the optimal and suboptimal TAS schemes are derived. The power allocation problem is formulated for performance optimization. Then the OP performance under different conditions is evaluated through numerical simulations to verify the analysis. The simulation results showed that optimal TAS scheme has a better OP performance than suboptimal TAS scheme; the power-allocation parameter has an important influence on the OP performance.

An Application of the Monte Carlo Method to the Economical Circuit Design in Consideration of the Drift Reliability (표류신뢰도를 고려한 경제적 회로 설계에 대한 몬테칼로법의 적용)

  • Kyun-Hyon Tchah
    • 전기의세계
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    • v.24 no.5
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    • pp.72-80
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    • 1975
  • In this paper an application of the Monte Carlo method to optimum circuit design is discussed. T. Tsuda and T. Kiyono's algorithm based on the Monte Carlo method for solving multiple simul-taneous nonlinear equations is generalized to apply it to finding solutions of the constrained nonlinear optimization problem. The generalized algorithm derived here is directly applied to economical circuit design. In the cirsuit design, the object function is a cost function which is related to the cost of each circuit component. The constraint is the variance of the total system expressed by the variances of each circuit component. The design is to be determined so that the circuit has specified drift reliability with minimum cost. A practical example of economical circuit design and a general nonlinear function minimization is presented with food results.

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Modality Conversion For Media QoS

  • Thang Truong Cong;Jung Yong Ju;Ro Yong Man
    • Proceedings of the IEEK Conference
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    • summer
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    • pp.395-399
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    • 2004
  • We present modality conversion as an effective means for QoS management. We show that modality conversion, in combination with content scaling, would give a wider range of adaptation to support QoS at media level. Here, we consider modality conversion with respect to resource constraint and human factor. To represent modality conversion as well as content scaling, we present the overlapped content value (OCV) model that relates the content value of different modalities with resources. The specification of user preference on modality conversion is divided into qualitative and quantitative levels. The user preference is then integrated into the OCV model so that modality conversion correctly reflects the user's wishes. For the conversion of multiple contents, an optimization problem is formulated and solved by dynamic programming. The experiments show that the proposed approach is efficient to be applied in practice.

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Optimizing Automated Stacking Crane Dispatching Strategy Using an MOEA for an Automated Container Terminal

  • Wu, Jiemin;Choe, Ri;Park, Tae-Jin;Ryu, Kwang-Ryel
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • 2011.06a
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    • pp.216-217
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    • 2011
  • The problem of automated stacking cranes (ASC) dispatching in container terminals is addressed in this paper. We propose a heuristic-based ASC dispatching approach which adopts multi-criteria decision strategy. By aggregating different criteria the proposed strategy can consider multiple aspects of the dispatching situation and make robust decision in various situations. A multi-objective evolutionary algorithm (MOEA) is adopted to tune the weights associated to each criteria to minimize both the quay crane delay and external truck delay. The proposed approach is validated by comparison with different dispatching heuristics and simulation results obtained confirms its effectiveness.

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Multiresponse Optimization through a Loss Function Considering Process Parameter Fluctuation (공정변수의 변동을 고려한 손실함수를 통한 다중반응표면 최적화)

  • Kwon, Jun-Bum;Lee, Jong-Seok;Lee, Sang-Ho;Jun, Chi-Hyuck;Kim, Kwang-Jae
    • Journal of Korean Institute of Industrial Engineers
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    • v.31 no.2
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    • pp.164-172
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    • 2005
  • A loss function approach to a multiresponse problem is considered, when process parameters are regarded as random variables. The variation of each response may be amplified through so called propagation of error (POE), which is defined as the standard deviation of the transmitted variability in the response as a function of process parameters. The forms of POE for each response and for a pair of responses are proposed and they are reflected in our loss function approach to determine the optimal condition. The proposed method is illustrated using a polymer case. The result is compared with the case where parameter fluctuation is not considered.

Identifying Temporal Pattern Clusters to Predict Events in Time Series

  • Heesoo Hwang
    • KIEE International Transaction on Systems and Control
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    • v.2D no.2
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    • pp.125-134
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    • 2002
  • This paper proposes a method for identifying temporal pattern clusters to predict events in time series. Instead of predicting future values of the time series, the proposed method forecasts specific events that may be arbitrarily defined by the user. The prediction is defined by an event characterization function, which is the target of prediction. The events are predicted when the time series belong to temporal pattern clusters. To identify the optimal temporal pattern clusters, fuzzy goal programming is formulated to combine multiple objectives and solved by an adaptive differential evolution technique that can overcome the sensitivity problem of control parameters in conventional differential evolution. To evaluate the prediction method, five test examples are considered. The adaptive differential evolution is also tested for twelve optimization problems.

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Optimization of Stochastic System Using Genetic Algorithm and Simulation

  • 유지용
    • Proceedings of the Korea Society for Simulation Conference
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    • 1999.10a
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    • pp.75-80
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    • 1999
  • This paper presents a new method to find a optimal solution for stochastic system. This method uses Genetic Algorithm(GA) and simulation. GA is used to search for new alternative and simulation is used to evaluate alternative. The stochastic system has one or more random variables as inputs. Random inputs lead to random outputs. Since the outputs are random, they can be considered only as estimates of the true characteristics of they system. These estimates could greatly differ from the corresponding real characteristics for the system. We need multiple replications to get reliable information on the system. And we have to analyze output data to get a optimal solution. It requires too much computation to be practical. We address the problem of reducing computation. The procedure on this paper use GA character, an iterative process, to reduce the number of replications. The same chromosomes could exit in post and present generation. Computation can be reduced by using the information of the same chromosomes which exist in post and present current generation.

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Optimal Operation of Reactive Power Compensation Devices for Voltage Control of Emegency Status (비상상태 전압제어를 위한 무효전력보상설비의 최적 운용)

  • Ahn, Chang-Han;Baek, Young-Sik
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.64 no.5
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    • pp.661-666
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    • 2015
  • This paper proposes a method for solving running cost problem by minimizing switching reactive power compensation devices. An objective function was modeled by calculating the weighting value of cost, and a solution was derived using ILP. This paper suggests optimal coordinative control method between FACTS, Shunt Reactors, Capacitors and OLTC. Therefore, it is valuable for decision maker in determining order and capacity of devices which gaining a voltage stabilization. As a result, the objectives of voltage stabilization and cost minimization were achieved simultaneously. This realizes the economic efficiency of the system. We start by showing how to solve systems of linear equations using the language of pivots and tableaus. The effectiveness of this technique is demonstrated in modified PSS/E MIGUM 45 bus system. The simulation results show the effectiveness of this algorithm by comparing the outcome withseveral established methods.

Solving Mixed Strategy Nash-Cournot Equilibria under Generation and Transmission Constraints in Electricity Market

  • Lee, Kwang-Ho
    • Journal of Electrical Engineering and Technology
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    • v.8 no.4
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    • pp.675-685
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    • 2013
  • Generation capacities and transmission line constraints in a competitive electricity market make it troublesome to compute Nash Equilibrium (NE) for analyzing participants' strategic generation quantities. The NE can cause a mixed strategy NE rather than a pure strategy NE resulting in a more complicated computation of NE, especially in a multiplayer game. A two-level hierarchical optimization problem is used to model competition among multiple participants. There are difficulties in using a mathematical programming approach to solve a mixed strategy NE. This paper presents heuristics applied to the mathematical programming method for dealing with the constraints on generation capacities and transmission line flows. A new formulation based on the heuristics is provided with a set of linear and nonlinear equations, and an algorithm is suggested for using the heuristics and the newly-formulated equations.

Mathematical Programming Models for Establishing Dominance with Hierarchically Structured Attribute Tree (계층구조의 속성을 가지는 의사결정 문제의 선호순위도출을 위한 수리계획모형)

  • Han, Chang-Hee
    • Journal of the military operations research society of Korea
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    • v.28 no.2
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    • pp.34-55
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    • 2002
  • This paper deals with the multiple attribute decision making problem when a decision maker incompletely articulates his/her preferences about the attribute weight and alternative value. Furthermore, we consider the attribute tree which is structured hierarchically. Techniques for establishing dominance with linear partial information are proposed in a hierarchically structured attribute tree. The linear additive value function under certainty is used in the model. The incompletely specified information constructs a feasible region of linear constraints and therefore the pairwise dominance relationship between alternatives leads to intractable non-linear programming. Hence, we propose solution techniques to handle this difficulty. Also, to handle the tree structure, we break down the attribute tree into sub-trees. Due to there cursive structure of the solution technique, the optimization results from sub-trees can be utilized in computing the value interval on the topmost attribute. The value intervals computed by the proposed solution techniques can be used to establishing the pairwise dominance relation between alternatives. In this paper, pairwise dominance relation will be represented as strict dominance and weak dominance, which ware already defined in earlier researches.