• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.32 no.3
• /
• pp.142-158
• /
• 2009

The supplier selection problem is perhaps the most important component of the purchasing function. Some of the common and influential criteria in the selection of a supplier include quality, price, delivery, and service. These evaluation criteria often conflict, however, and it is frequently impossible to find a supplier that excels in all areas. In addition, some of the criteria are quantitative and some are qualitative. Thus, a methodology is needed that can capture both subjective and objective evaluation measures. The Analytic Hierarchy Process(AHP) is a decision-making method for ranking alternative courses of action when multiple criteria must be considered. This paper proposes the AHP-based approach which can structure the supplier selection process and the achievements-based procedure which can allocate order quantities for the selected suppliers In automotive part manufacturers. Also, through the practical case of 'D' automotive part manufacturing company, we shows that the proposed AHP based supplier selection approach and the achievements-based allocation procedure of order quantity can be successfully applied for supplier selection and order quantity allocation problems.

• The KIPS Transactions:PartB
• /
• v.11B no.5
• /
• pp.611-618
• /
• 2004

This paper addresses the design and implementation of class distribution in distributed object-oriented databases. The proposed strategy of distribution consists of two-step design of fragments. One is class fragmentation and the other is allocation of fragments. In step of class fragmentation, we have defined partitioning algorithms to reflect the characteristics of object-oriented databases such as method, inheritance and composite-object. In step of allocation, we have defined the objective function for allocation considering system operating cost including storage, query processing and communication and implemented it using Genetic Algorithm.

• Advances in Energy Research
• /
• v.6 no.1
• /
• pp.55-73
• /
• 2019

The cost incurred by voltage sag effect in power networks has always been of important concern for discussions. Due to the environmental constraints, fossil fuel shortage crisis and low efficiency of conventional power plants, decentralized generation and renewable based DG have become trends in recent decades; because DGs can reduce the voltage sag effect in distribution networks noticeably; therefore, optimum allocation of DGs in order to maximize their effectiveness is highly important in order to maximize their effectiveness. In this paper, a new method is proposed for calculating the cost incurred by voltage sag effect in power networks. Thus, a new objective function is provided that comprehends technical standards as minimization of the cost incurred by voltage sag effect, active power losses and economic criterion as the installation and maintenance costs of DGs. Considering operational constraints of the system, the optimum allocation of DGs is a constrained optimization problem in which Lightning Attachment procedure optimization (LAPO) is used to resolve it and is the optimum number, size and location of DGs are determined in IEEE 33 bus test system and IEEE 34 bus test system. The results show that optimum allocation of DGs not only reduces the cost incurred by voltage sag effect, but also improves the other characteristics of the system.

• ETRI Journal
• /
• v.44 no.3
• /
• pp.400-412
• /
• 2022

In cognitive radio networks (CRNs), the computational complexity of resource allocation algorithms is a significant problem that must be addressed. However, the high computational complexity of the optimal solution for tackling resource allocation in CRNs makes it inappropriate for use in practical applications. Therefore, this study proposes a power-based pricing algorithm (PPA) primarily to reduce the computational complexity in downlink CRN scenarios while restricting the interference to primary users to permissible levels. A two-stage approach reduces the computational complexity of the proposed mathematical model. Stage 1 assigns subcarriers to the CRN's users, while the utility function in Stage 2 incorporates a pricing method to provide a power algorithm with enhanced reliability. The PPA's performance is simulated and tested for orthogonal frequency-division multiplexing-based CRNs. The results confirm that the proposed algorithm's performance is close to that of the optimal algorithm, albeit with lower computational complexity of O(M log(M)).

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.17 no.5
• /
• pp.25-33
• /
• 2017

NOMA (Non-orthogonal multiple access) system becoming a strong candidate for 5G cellular system of its high spectral efficiency. This paper considers an optimal power allocation scheme to minimize the outage probability of a user relay based cooperative NOMA system. We first derive the outage probabilities of the relay user (RU) and the destination user (DU) with selection combining. Based on these probabilities, the outage probability of the cooperative NOMA system is obtained. The analytical results are verified by Monte Carlo simulation. It is noticed that the outage probability of cooperative NOMA system has a convex function, the optimum power allocation coefficient, which satisfied the minimum outage probability, is calculated. Numerical examples show that the optimal power allocation coefficient increases with the required capacity of DU. While the capacity of DU is fixed, we noticed that the increase of the required capacity of RU decreases the optimal power allocation coefficient.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.7 no.12
• /
• pp.2957-2986
• /
• 2013

The traditional approach of fixed spectrum allocation to licensed networks has resulted in spectrum underutilisation. Cognitive radio technology is envisioned as a promising solution that can be used to resolve the ineffectiveness of the fixed spectrum allocation policy by accessing the underutilised spectrum of existing technologies opportunistically. The implementation of cognitive radio networks (CRNs) faces distinct challenges due to the fact that two systems (i.e., cognitive radio (CR) and primary users (PUs)) with conflicting interests interact with each other. Specially, in self-organised systems such as ad-hoc CRNs (AHCRNs), the coordination of spectrum access introduces challenges to researchers due to rapid utilisation changes in the available spectrum, as well as the multi-hop nature of ad-hoc networks, which creates additional challenges in the analysis of resource allocation (e.g., power control, channel and rate allocation). Instead, game theory has been adopted as a powerful mathematical tool in analysing and modelling the interaction processes of AHCRNs. In this survey, we first review the most fundamental concepts and architectures of CRNs and AHCRNs. We then introduce the concepts of game theory, utility function, Nash equilibrium and pricing techniques. Finally, we survey the recent literature on the game theoretic analysis of AHCRNs, highlighting its applicability to the physical layer PHY, the MAC layer and the network layer.

• 한국정보통신설비학회:학술대회논문집
• /
• 2009.08a
• /
• pp.382-386
• /
• 2009

Online or sequential learning is one of the most basic and powerful method to train neuron network, and it has been widely used in disease detection, weather prediction and other realistic classification problem. At present, there are many algorithms in this area, such as MRAN, GAP-RBFN, OS-ELM, SVM and SMC-RBF. Among them, SMC-RBF has the best performance; it has less number of hidden neurons, and best efficiency. However, all the existing algorithms use signal normal distribution as kernel function, which means the output of the kernel function is same at the different direction. In this paper, we use multi-variable normal distribution as kernel function, and derive EKF learning formulas for multi-variable normal distribution kernel function. From the result of the experience, we can deduct that the proposed method has better efficiency performance, and not sensitive to the data sequence.

• Journal of Korea Multimedia Society
• /
• v.11 no.8
• /
• pp.1072-1081
• /
• 2008

We can categorize the network address allocation mechanism into two types. One is to assign a unique network address using the address allocation server and the other is to make a random address by itself and process the DAD(Duplicate Address Detection) procedure. In this paper we suggest a new address allocation mechanism based on the signal strength for the PLC-based home network. As the combined mechanism of two types this mechanism allocates a unique address for the new node from one of the existing nodes with the simple equation and with the priority based on the signal strength from the new node to the existing nodes. We can use this mechanism for the self-healing function when the packet from the source node may not be delivered to the destination node directly. We developed the simulator for our mechanism using the C# programming and verified the network address assigned uniquely based on the signal strength.

• The KIPS Transactions:PartA
• /
• v.8A no.3
• /
• pp.279-286
• /
• 2001

This paper proposes a low power resource allocation and scheduling algorithm that minimized power consumption such as DSP circuit in high-level synthesis process. In this paper, we have used list-scheduling method for low power design in scheduling step. Also, it increase possibility to reuse input through resource sharing when assign resource. After scheduling, the resources allocation uses the power function in consideration of the result of calculating average hamming distances and switching activity between two input. First, it obtain switching activity about input value after calculate average hamming distances between two operator and find power value make use of bit pattern of the input value. Resource allocation process assign operator to minimize average hamming distance and power dissipation on all occasions which is allocated at each control step according to increase control step. As comparing the existed method, the execution time becomes fast according to number of operator and be most numberous control step. And in case of power that consume, there is decrease effect from 6% to 8% to be small.

• Journal of the Korean Statistical Society
• /
• v.22 no.2
• /
• pp.235-247
• /
• 1993

The predictive density function of a potential future observation and its first four moments are obtained in this paper to study the effects of a non-normal prior of the unknown mean of a normal population. The derived predictive density function is modified to study changes in utility curves, used to choose the optimum treatment from a given set of treatments, at a given level of stimulus due to slight deviations from normality of the prior distribution. Numerical illustrations are provided to exhibit some effectsl.