• ETRI Journal
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• v.41 no.5
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• pp.626-636
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• 2019

A novel algorithm for joint user selection and optimal power allocation for Stackelberg game-based revenue maximization in a downlink non-orthogonal multiple access (NOMA) network is proposed in this study. The condition for the existence of optimal solution is derived by assuming perfect channel state information (CSI) at the transmitter. The Lagrange multiplier method is used to convert the revenue maximization problem into a set of quadratic equations that are reduced to a regular chain of expressions. The optimal solution is obtained via a univariate iterative procedure. A simple algorithm for joint optimal user selection and power calculation is presented and exhibits extremely low complexity. Furthermore, an outage analysis is presented to evaluate the performance degradation when perfect CSI is not available. The simulation results indicate that at 5-dB signal-to-noise ratio (SNR), revenue of the base station improves by at least 15.2% for the proposed algorithm when compared to suboptimal schemes. Other performance metrics of NOMA, such as individual user-rates, fairness index, and outage probability, approach near-optimal values at moderate to high SNRs.

• The Korean Journal of Applied Statistics
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• v.28 no.3
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• pp.467-475
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• 2015

Accurate demand forecasting is a crucial component in revenue management(RM). The booking data of departed flights is used to forecast the demand for future departing flights; however, some booking requests that were denied were omitted in the departed flights data. Denied booking requests can be interpreted as censored in statistics. Thus, unconstraining demand is an important issue to forecast the true demands of future flights. Several unconstraining methods have been introduced and a method based on expectation maximization is considered superior. In this study, we propose a new unconstraining method based on a regression model that can entertain such censored data. Through a simulation study, the performance of the proposed method was evaluated with two representative unconstraining methods widely used in RM.

• Journal of the Korean Operations Research and Management Science Society
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• v.34 no.3
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• pp.55-69
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• 2009

It is often to apply revenue sharing models in rental industries which consist of a retailer and a wholesaler. This research analyzed the influences to profit of the supply chain if we adopt the revenue sharing model when the demand is uncertain and price sensitive. We found the conditions of the revenue sharing model to maximize the profit of the supply chain, and identified incentive compatible conditions for revenue sharing. It is proved that vertical integration guarantees maximization of profit for the supply chain. Also we found that it is possible to derive Incentive compatible schemes by controlling ranges of revenue sharing ratios.

• Management Science and Financial Engineering
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• v.18 no.1
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• pp.13-20
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• 2012

This paper considers a revenue maximization problem on a single processor. Each job is identified as its processing time, initial reward, reward decreasing rate, and preferred start time. If the processor starts a job at time zero, revenue of the job is its initial reward. However, the revenue decreases linearly with the reward decreasing rate according to its processing start time till its preferred start time and finally its revenue is zero if it is started the processing after the preferred time. Our objective is to find the optimal sequence which maximizes the total revenue. For the problem, we characterize the optimal solution properties and prove the NP-hardness. Based upon the characterization, we develop a branch-and-bound algorithm for the optimal sequence and suggest five heuristic algorithms for efficient solutions. The numerical tests show that the characterized properties are useful for effective and efficient algorithms.

• Journal of the Korean Institute of Landscape Architecture
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• v.24 no.3
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• pp.109-114
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• 1996

Generally, the size of our recreation sites is selected through use demand at the peak day. At same time, scale economic and diseconomic are applied to a recreation site. If you are a rational decision-maker, you would like to select the size of your park at profit-maximization point. This study is the first try for modelling a Gain-Loss by the size options of a theme park. For testing the validity of a financial model to select the size of theme parks. Ever-Land, Seoul-Land, Dream-Land's operating size was analyzed. By the size options, the revenue of each park was compared with cost. The profit-maximization point and break-even point of each park were found. Ever-Land and Dream-Land's size was selected between the profit-maximization point and the break-even point. In contrast with Ever-Land and Dream-Land's, Seoul-Land's was selected upper the break-even point. To increase the utility of this model in selecting the size of a theme park, a decision-maker must keep in mind a few limits of this study. That is, 1) this model can not be applied at public parks. 2) Sometimes the others can be more important than financial revenue and cost. Finally, there is the validity of Gain-Loss Model in estimating only the financial revenues and costs through the size options.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.5
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• pp.976-998
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• 2011

This paper attempts to maximize the operator's revenue while simultaneously providing a multi-constraint, multi-hop and deterministic QoS provisioning for real time traffic in IEEE 802.16m based 4G networks. The optimal solution to such a problem is NP-complete and therefore not feasible to be solved in a tolerable polynomial time. For this reason, we also provide a simple price based greedy heuristic to be used along with the admission control. Simulation results for different QoS schemes show that the heuristic produces a revenue that is very close to the optimal revenue, and is far more aggressive than the size based and other common algorithms that are computationally feasible to be implemented in IEEE 802.16m.

• Journal of Communications and Networks
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• v.6 no.1
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• pp.68-77
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• 2004

In the near future packet networks should support applications which can not predict their traffic requirements in advance, but still have tight quality of service requirements, e.g., guaranteed bandwidth, jitter, and packet loss. These dynamic characteristics mean that the sources can be made to modify their data transfer rates according to network conditions. Depending on the customer&; needs, network operator can differentiate incoming connections and handle those in the buffers and the interfaces in different ways. In this paper, dynamic QoS-aware scheduling algorithm is presented and investigated in the single node case. The purpose of the algorithm is in addition to fair resource sharing to different types of traffic classes with different priorities ?to maximize revenue of the service provider. It is derived from the linear type of revenue target function, and closed form globally optimal formula is presented. The method is computationally inexpensive, while still producing maximal revenue. Due to the simplicity of the algorithm, it can operate in the highly nonstationary environments. In addition, it is nonparametric and deterministic in the sense that it uses only the information about the number of users and their traffic classes, not about call density functions or duration distributions. Also, Call Admission Control (CAC) mechanism is used by hypothesis testing.

• Industrial Engineering and Management Systems
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• v.9 no.2
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• pp.97-106
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• 2010

Can eBay.com's fee structure coordinate the channel? It's a critical strategic problem in e-commerce operations and an interesting research hypothesis as well. eBay's fees include three parts: monthly subscription fee, insertion fee, and final value fee (i.e., a revenue sharing portion), which represent a generic form of revenue sharing fee structure between the retailer and the vendor in a supply chain. This research deals with such a channel consisting of a price-setting vendor who sells products through eBay's marketplace exclusively to the end customers. The up- and down-stream channel relationship is consignment-based revenue sharing. We use a game-theoretic approach with assumption of the retailer (i.e., eBay.com) being a Stackelberg-leader and the vendor being a follower. The Stackelberg-leader decides on the terms of revenue sharing contract (i.e., fee structure), and the follower (vendor) decides on how many units to sell and the items' selling price. This study formulates several profit-maximization models by considering the effects of the retail price on the demand function. Under such settings, we show that eBay's fee structure can improve the channel efficiency; yet it cannot coordinate the channel optimally.

• Journal of the Korean Society of Industry Convergence
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• v.8 no.2
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• pp.85-95
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• 2005

The margin level in the futures market platys an important role in balancing the default probability with the investor's opportunity cost. In this paper, we investigate whether the movement of KOSPI200 futures daily prices can be modeled with the extreme value theory. Based on this investigation, we examine the validity of the margin level set by the extreme value theory. Moreover, we propose an expected profit-maximization model for securities companies. In this model, the extreme value theory is used for cost estimation, and a regression analysis is used for revenue calculation. Computational results are presented to compare the extreme value distribution with the empirical distribution of margin violation in KOSPI200 and to examine the suitability of the expected profit-maximization model.

• Journal of the military operations research society of Korea
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• v.11 no.2
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• pp.64-68
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• 1985

This paper considers the following case: (1) the product is paid by the right price for a lot accepted by a given consumer's acceptance sampling plan, and (2) the product is paid by the discounted price for a lot rejected by this plan. In such a case, the producer's sampling plan need not be the same as that of the consumer's. From the producer's view point, the producer need to determine the preliminary sample size which maximizes his revenue. This paper, therefore, determines an optimal preliminary sample size from the producer's view point. This preliminary sample size is affected by the consumer's acceptance sampling plan, percent defective, preliminary inspection cost and the discount rate of the price.