• Korean Management Science Review
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• v.31 no.3
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• pp.113-130
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• 2014

Cooperative coevolutionary algorithm (CCEA) has proven to be a very powerful means of solving optimization problems through problem decomposition. CCEA implies the use of several populations, each population having the aim of finding a partial solution for a component of the considered problem. Populations evolve separately and they interact only when individuals are evaluated. Interactions are made to obtain complete solutions by combining partial solutions, or collaborators, from each of the populations. In this respect, we can think of various interaction modes. The goal of this research is to develop a CCEA for a supply chain network design (SCND) problem and identify which interaction mode gives the best performance for this problem. We present general design principle of CCEA for the SCND problem, which require several co-evolving populations. We classify these populations into two groups and classify the collaborator selection scheme into two types, the random-based one and the best fitness-based one. By combining both two groups of population and two types of collaborator selection schemes, we consider four possible interaction modes. We also consider two modes of updating populations, the sequential mode and the parallel mode. Therefore, by combining both four possible interaction modes and two modes of updating populations, we investigate seven possible solution algorithms. Experiments for each of these solution algorithms are conducted on a few test problems. The results show that the mode of the best fitness-based collaborator applied to both groups of populations combined with the sequential update mode outperforms the other modes for all the test problems.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.2
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• pp.65-74
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• 2009

In optimizing the neural network structure, there are two methods of the pruning scheme and the constructive scheme. In this paper we use the pruning scheme to optimize neural network structure, and the genetic algorithm to find out its optimum node pruning. In the conventional researches, the input and hidden layers were optimized separately. On the contrary we attempted to optimize the two layers simultaneously by encoding two layers in a chromosome. The offspring networks inherit the weights from the parent. For teaming, we used the existing error back-propagation algorithm. In our experiment with various databases from UCI Machine Learning Repository, we could get the optimal performance when the network size was reduced by about $8{\sim}25%$. As a result of t-test the proposed method was shown better performance, compared with other pruning and construction methods through the cross-validation.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.10 no.3
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• pp.419-429
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• 1999

Identifying the boundary of the effective receiving power of waves is one of the most important factors for cell optimization. In this paper, we introduce a propagation loss prediction model which yields highly accurate prediction in very complex areas as Seoul where a mixture of many large buildings, small buildings, broad streets, narrow alleys, rivers and forests co-exist in an irregular arrangement. This prediction model is based on neural networks trained on field measurement data collected in the past. Using these data along with 3-D digital elevation maps and vector data for building structures, we extract the parameter values which mainly affect the amount of propagation loss. These parameter values are then used as the inputs to the neural network. Trained neural network becomes the approximated function of the propagation loss model which generalizes very well and can predict accurately in the regions not included in training the neural network. The experimental results show a superior performance over the other models in the cells operating in the city of Seoul.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.6
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• pp.1330-1336
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• 2014

QoS techniques and transmitted in real-time communication with the advancement of technology a variety of applications and services are available these days, mobile devices bogeuphwa LTE technology to the development of multimedia services with high quality can be realized. In order to satisfy this condition simply with a router with an increased bandwidth expansion by considering the increase in the routing table of the network scalability problems included. Burst traffic data to be distributed according to the environment is to be centered. To do this, the destination -based routing method to transmit the current paper -based (Source routing) routing settings are required. In this paper, published by the IETF, IP switching system based on standardized protocol Label Switching Multi-Protocol Label Switching (MPLS) network by using the existing Best Effect is difficult to guarantee QoS for multimedia transmission in MPLS network environment using optimized QoS guarantees to transmit the multicast.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.6
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• pp.644-651
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• 1997

In the water purification plant, chemicals are injected for quick purification of raw water. It is clear that the amount of chemicals intrinsically depends on water quality such as turbidity, temperature, pH and alkalinity. However, the process of chemical reaction to improve water quality (e.g., turbidity) by chemicals is not yet fully clarified nor quantified. The feedback signal in the process of coagulant dosage, which should be measured (through the sensor of the plant) to compute the appropriate amount of chemicals, is also not available. Most traditional methods focus on judging the conditions of purifying reaction and determine the amounts of chemicals through manual operation of field experts using Jar-test data. In this paper, a systematic control strategy is proposed to derive the optimum dosage of coagulant, PAC(Polymerized Aluminium Chloride), using Jar-test results. A neural network model is developed for coagulant dosing and purifying process by means of six input variables (turbidity, temperature, pH, alkalinity of raw water, PAC feed rate, turbidity in flocculation) and one output variable, while considering the relationships to the reaction of coagulation and flocculation. The model is utilized to derive the optimum coagulant dosage (in the sense of minimizing turbidity of water in flocculator). The ability of the proposed control scheme validated through the field test has proved to be of considerable practical value.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.11 no.2
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• pp.108-121
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• 1986

In this paper, the development of a simulator for the performance estimation and parameter optimization of an integrates voice/data packet communication network is described. The simulator implemented is capable of simulating the integrated voice/data network that handles packet voice terminals as well as data terminals and hosts operating under standard CCITT protocols. Of the three descrete event simulation approaches presently known, the process interaction method has been chose. With this approach one can implement a simulator that is related most Closely with the real system. The simulator has been implemented in PL/I and GPSS simulation languages, resulting in a software package of about 4,000 lines. To reduce the computer run time of the simulator, we have used a method of reducing conditional events based on a GPSS LINK block. We describe various aspects of the simulation model developed. We then investigate the performance of a 7-node network using the simulator, and present the results. For validation of the simulator developed, we construct a simulation model for a simple voice/ data multiplexer, and compare the results of simulation with those of an analytical model.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.1A
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• pp.76-83
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• 2009

In this paper, we provide opportunistic scheduling schemes for elastic services in OFDMA systems with fairness constraints for each user. We adopt the network utility maximization framework in which a utility function is defined for each user to represent its level of satisfaction to the service. Since we consider elastic services whose degree of satisfaction depends on its average data rate, we define the utility function of each user as a function of its average data rate. In addition, for fair resource allocation among users, we define fairness requirements of each user by using utility functions. We first formulate an optimization problem for each fairness requirement that aim at maximizing network utility, which is defined as the sum of utilities of users. We then develop an opportunistic scheduling scheme for each fairness requirement by solving the problem using a dual approach and a stochastic sub-gradient algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.9
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• pp.764-774
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• 2013

The number of users and data packets has increased in 4G cellular networks. Therefore, 4G cellular network providers suffer from the network capacity problem. In order to solve this problem, femtocell concept is suggested. It can reduce the coverage hole and enhance the QoS. However, only small number of femtocells experience the large amount of loads. To solve this problem, Mobility Load Balancing (MLB) algorithm is suggested, which is a kind of load balancing algorithm. To distribute the traffic load, MLB algorithm modifies the handover region. If the handover region is reduced by MLB algorithm, some cell edge users are compulsively handed over to neighbor femtocell. In this paper, we analyze the relation between MLB performing period and performance indicators. For example throughput and blocking probability is reduced, if period is decreased. On the contrast, if period is increased, the number of handover frequency is decreased. Using this relation, we suggest the adaptive periodic MLB algorithm. This algorithm includes the advantage of both long period and short period MLB algorithm, such as high throughput, the small number of handover frequency, and low blocking probability.

• KIPS Transactions on Computer and Communication Systems
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• v.7 no.8
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• pp.203-210
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• 2018

Mobile traffic is increasing consistently, and mobile carriers are becoming more and more hard to meet this ever-increasing mobile traffic demand by means of additional installation of base stations. To overcome this problem, heterogeneous networks, which can reuse space and frequency by installing small cells such as femto cells in existing macro cells, were introduced. However, existing macro cell users are difficult to increase the spectral efficiency without the cooperation of femto owners. Femto owners are also reluctant to accommodate other mobile stations in their femto stations without proper incentive. In this paper, a method of obtaining the optimal incentive is proposed, which adopts a utility function based on the logarithm of throughput of mobile stations, and the incentive is calculated to maximize the utility of the entire network.

• Journal of Korean Society of Transportation
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• v.19 no.6
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• pp.143-160
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• 2001

Micro-simulation models have been recognized as an efficient assessment tool in developing traffic signal control technologies. In this paper a prototype of a microscopic simulation model which can be applied to evaluate the performance of traffic-adaptive signal control strategies was developed. In the simulation process, space-based arrays were appled to estimate parameters of car following and lane changing models. Two levels of link types, a micro-type and macro-type links, were also embodied in the simulation process. The proposed model was tested on a test network consists of 9 intersections. The performance of the proposed model was evaluated in link by link comparisons with the results of NETSIM. The results show that the proposed model could appropriately simulate traffic flows of the test network. The model also produces traffic adaptive signal timings, cycle lengths and green times for turning movements, based on the detector data. It implies that the optimization process of the model produces reasonable signal timings for the test network on the cycle basis.