• Journal of Electrical Engineering and Technology
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• v.3 no.4
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• pp.509-513
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• 2008

In this paper, we investigate how generators' ramp-rate constraints may influence their equilibrium strategy formulation. In the market model proposed in this study, the generators' ramp-rate constraints are explicitly represented. In order to fully characterize the inter-temporal nature of the ramp-rate constraints, a dynamic game model is presented. The subgame perfect Nash equilibrium is adopted as the solution of the game and the backward induction procedure for the solution of the game is designed in this paper. The inter-temporal nature of the ramp-rate constraints results in the Markov property of the game, and we have found that the Markov property of the game significantly simplifies the subgame perfect Nash equilibrium characterization. Finally, a simple electricity market numerical illustration is presented for the successful application of the approach proposed.

• ETRI Journal
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• v.29 no.2
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• pp.201-211
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• 2007

This paper focuses on the scheduling problem with the objective of maximizing system throughput, while guaranteeing long-term quality of service (QoS) constraints for non-realtime data users and short-term QoS constraints for realtime multimedia users in multiclass service high-speed uplink packet access (HSUPA) systems. After studying the feasible rate region for multiclass service HSUPA systems, we formulate this scheduling problem and propose a multi-constraints HSUPA opportunistic scheduling (MHOS) algorithm to solve this problem. The MHOS algorithm selects the optimal subset of users for transmission at each time slot to maximize system throughput, while guaranteeing the different constraints. The selection is made according to channel condition, feasible rate region, and user weights, which are adjusted by stochastic approximation algorithms to guarantee the different QoS constraints at different time scales. Simulation results show that the proposed MHOS algorithm guarantees QoS constraints, and achieves high system throughput.

• Journal of Communications and Networks
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• v.11 no.3
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• pp.297-305
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• 2009

Multiprotocol label switching (MPLS) networks require dynamic flow admission control to guarantee end-to-end quality of service (QoS) for each Internet protocol (IP) traffic flow. In this paper, we propose to tackle the joint routing and admission control problem for the IP traffic flows in MPLS networks without rerouting already admitted flows. We propose two mathematical programming models for this problem. The first model includes end-to-end delay constraints and the second one, end-to-end packet loss constraints. These end-to-end QoS constraints are imposed not only for the new traffic flow, but also for all already admitted flows in the network. The objective function of both models is to minimize the end-to-end delay for the new flow. Numerical results show that considering end-to-end delay (or packet loss) constraints for all flows has a small impact on the flow blocking rate. Moreover, we reduces significantly the mean end-to-end delay (or the mean packet loss rate) and the proposed approach is able to make its decision within 250 msec.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.17 no.2
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• pp.115-128
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• 2013

The optimal portfolio selection problem under inflation risk and subsistence constraints is considered. There are index bonds to invest in financial market and it helps to hedge the inflation risk. By applying the martingale method, the optimal consumption rate and the optimal portfolios are obtained explicitly. Furthermore, the quantitative effect of inflation risk and subsistence constraints on the optimal polices are also described.

• Korean Journal of Chemical Engineering
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• v.36 no.3
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• pp.356-367
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• 2019

This work presents an advanced and systematic approach to analytically design the optimal parameters of a two parameter second-order internal model control (IMC) filter that satisfies operational constraints on the output process, the manipulated variable as well as rate of change of the manipulated variable, for a first-order plus dead time (FOPDT) process. The IMC parameters are designed to minimize a control objective function composed of the weighted sum of the error between the process variable and the set point, and the rate of change of the manipulated variable, and to satisfy the desired constraints. The feasible region of the constrained IMC control parameters was graphically analyzed, as the process parameters and the constraints varied. The resulting constrained IMC control parameters were also used to find the corresponding industrial proportional-integral controller parameters of a Smith predictor structure.

• Journal of Communications and Networks
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• v.16 no.2
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• pp.130-139
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• 2014

Due to the unpredictable nature of channel availability, carrying delay-sensitive traffic in cognitive radio networks (CRNs) is very challenging. Spectrum leasing of radio resources has been proposed in the so called coordinated CRNs to improve the quality of service (QoS) experienced by secondary users (SUs). In this paper, the performance of coordinated CRNs under fixed-rate with hard-delay-constraints traffic is analyzed. For the adequate and fair performance comparison, call admission control strategies with fractional channel reservation to prioritize ongoing secondary calls over new ones are considered. Maximum Erlang capacity is obtained by optimizing the number of reserved channels. Numerical results reveal that system performance strongly depends on the value of the mean secondary service time relative to the mean primary service time. Additionally, numerical results show that, in CRNs without spectrum leasing, there exists a critical utilization factor of the primary resources from which it is not longer possible to guarantee the required QoS of SUs and, therefore, services with hard delay constraints cannot be even supported in CRNs. Thus, spectrum leasing can be essential for CRN operators to provide the QoS demanded by fixed-rate applications with hard delay constraints. Finally, the cost per capacity Erlang as function of both the utilization factor of the primary resources and the maximum allowed number of simultaneously rented channels is evaluated.

• Journal of the Korean Operations Research and Management Science Society
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• v.28 no.4
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• pp.1-19
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• 2003

This paper studies power and rate control for data users on the forward link of CDMA system with two cells. The QoS for data users is specified by delay and error rate constraints as well as a family of utility functions representing system throughput and fairness among data users. Optimal power and rate allocation problem is mathematically formulated as a nonlinear programming problem, which is to maximize total utility under delay and error rate constraints, and optimal power and rate allocation scheme (OPRAS) is proposed to obtain a good solution in a fast time. Computational experiments show that the proposed scheme OPRAS works very well and increases total utility compared to the separate power and rate allocation scheme (SPARS) which considers each cell individually.

• Journal of Electrical Engineering and Technology
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• v.10 no.5
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• pp.1940-1949
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• 2015

This paper presents an Enhanced Particle Swarm Optimization (EPSO) to solve short-term hydrothermal scheduling (STHS) problem with non-convex fuel cost function and a variety of operational constraints related to hydro and thermal units. The operators of the conventional PSO are dynamically controlled using exponential functions for better exploration and exploitation of the search space. The overall methodology efficiently regulates the velocity of particles during their flight and results in substantial improvement in the conventional PSO. The effectiveness of the proposed method has been tested for STHS of two standard test generating systems while considering several operational constraints like system power balance constraints, power generation limit constraints, reservoir storage volume limit constraints, water discharge rate limit constraints, water dynamic balance constraints, initial and end reservoir storage volume limit constraints, valve-point loading effect, etc. The application results show that the proposed EPSO method is capable to solve the hard combinatorial constraint optimization problems very efficiently.

• IE interfaces
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• v.12 no.2
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• pp.337-345
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• 1999

This paper presents the optimization of a drilling operation subject to machining constraints such as power, torque, thrust, speed and feed rate. The optimization is meant to minimize the machining time required to produce a hole. For the first time, the effects of a pilot hole are included in the formulation of the machining constraints. The optimization problem is solved by using the geometric programming technique. The dual problem is simplified based on the characteristics of the problem, and the effects of machining constraints on the machining variables are identified.

• Journal of Astronomy and Space Sciences
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• v.25 no.4
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• pp.361-374
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• 2008

Recently, satellite formation flying has been a topic of significant research interest in aerospace society because it provides potential benefits compared to a large spacecraft. Some techniques have been proposed to design optimal formation trajectories minimizing fuel consumption in the process of formation configuration or reconfiguration. In this study, a method is introduced to build fuel-optimal trajectories minimizing a cost function that combines the total fuel consumption of all satellites and assignment of fuel consumption rate for each satellite. This approach is based on collocation and nonlinear programming to solve constraints for collision avoidance and the final configuration. New constraints of nonlinear equality or inequality are derived for final configuration, and nonlinear inequality constraints are established for collision avoidance. The final configuration constraints are that three or more satellites should form a projected circular orbit and make an equilateral polygon in the horizontal plane. Example scenarios, including these constraints and the cost function, are simulated by the method to generate optimal trajectories for the formation configuration and reconfiguration of multiple satellites.