• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.12
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• pp.3133-3151
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• 2012

The optimal price strategy selection of two bounded rational cognitive mobile virtual network operators (MVNOs) in a duopoly spectrum sharing market is investigated. The bounded rational operators dynamically compete to sell the leased spectrum to secondary users in order to maximize their profits. Meanwhile, the secondary users' heterogeneous preferences to rate and price are taken into consideration. The evolutionary game theory (EGT) is employed to model the dynamic price strategy selection of the MVNOs taking into account the response of the secondary users. The behavior dynamics and the evolutionary stable strategy (ESS) of the operators are derived via replicated dynamics. Furthermore, a reward and punishment mechanism is developed to optimize the performance of the operators. Numerical results show that the proposed evolutionary algorithm is convergent to the ESS, and the incentive mechanism increases the profits of the operators. It may provide some insight about the optimal price strategy selection for MVNOs in the next generation cognitive wireless networks.

• Computers and Concrete
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• v.11 no.6
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• pp.541-569
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• 2013

There is a wide variety of existing Genetic Algorithms (GA) operators and parameters in the literature. However, there is no unique technique that shows the best performance for different classes of optimization problems. Hence, the evaluation of these operators and parameters, which influence the effectiveness of the search process, must be carried out on a problem basis. This paper presents a comparison for the influence of GA operators and parameters on the performance of the damage identification problem using the finite element model updating method (FEMU). The damage is defined as reduction in bending rigidity of the finite elements of a reinforced concrete beam. A certain damage scenario is adopted and identified using different GA operators by minimizing the differences between experimental and analytical modal parameters. In this study, different selection, crossover and mutation operators are compared with each other based on the reliability, accuracy and efficiency criteria. The exploration and exploitation capabilities of different operators are evaluated. Also a comparison is carried out for the parallel and sequential GAs with different population sizes and the effect of the multiple use of some crossover operators is investigated. The results show that the roulettewheel selection technique together with real valued encoding gives the best results. It is also apparent that the Non-uniform Mutation as well as Parent Centric Normal Crossover can be confidently used in the damage identification problem. Nevertheless the parallel GAs increases both computation speed and the efficiency of the method.

• Journal of Korean Institute of Industrial Engineers
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• v.20 no.3
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• pp.15-34
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• 1994

This paper considers the genetic algorithms(GAs) for the mixed model assembly line sequencing(MMALS) in which the objective is to minimize the overall line length. To apply the GAs to the MMALS, the representation, selection, genetic sequencing operators, and genetic parameters are studied. Especially, the existing sequencing binary operators such as partially map crossover(PMX), cycle crossover(CX), and order crossover (OX) are modified to be suitable for the MMALS, and a new sequencing binary operator called immediate successor relationship crossover (ISR) is introduced. These binary operators mentioned above and/or unary operators such as swap, insertion, inversion, displacement, and splice are compared to find operators which work well in the MMALS. Experimental results indicate that 1) among the binary operators ISR operator is the best, followed by the modified OX, and the modified PMX, with the modified CX being the worst, 2) among the unary operators inversion operator is the best, followed by displacement, swap, and insertion, with splice being the worst, and 3) in general, the unary operators perform better than the binary operators for the MMALS.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.6
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• pp.849-855
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• 2008

The Diagnostic Unit of CLINAID can infer working diagnoses for general diseases from the information provided by a user. This user-provided information in the form of signs and symptoms, however, is usually not sufficient to make a final decision on a working diagnosis. In order for the Diagnostic Unit to reach a diagnostic conclusion, it needs to select suitable clinical investigations for the patients. Because different investigations can be selected for the same patient, we need a process that can optimize the selection procedure employed by the Diagnostic Unit. This process, called a selection algorithm, must work with the fuzzy relational method because CLINAID uses fuzzy relational structures extensively for its knowledge bases and inference mechanism. In this paper we present steps of the selection algorithm along with simulation results on this algorithm using fuzzy relational products, both harsh product and mean product. The computation results of applying several different fuzzy implication operators are compared and analyzed.

• Korean Journal of Mathematics
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• v.29 no.1
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• pp.137-167
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• 2021

Spherical fuzzy set (SFS) is also one of the fundamental concepts for address more uncertainties in decision problems than the existing structures of fuzzy sets, and thus its implementation was more substantial. The well-known sine trigonometric function maintains the periodicity and symmetry of the origin in nature and thus satisfies the expectations of the experts over the multi parameters. Taking this feature and the significance of the SFSs into the consideration, the main objective of the article is to describe some reliable sine trigonometric laws (ST L) for SFSs. Associated with these laws, we develop new average and geometric aggregation operators to aggregate the Spherical fuzzy numbers (SFNs). Then, we presented a group decision- making (DM) strategy to address the multi-attribute group decision making (MAGDM) problem using the developed aggregation operators. In order to verify the value of the defined operators, a MAGDM strategy is provided along with an application for the selection of laptop. Moreover, a comparative study is also performed to present the effectiveness of the developed approach.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.5
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• pp.563-570
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• 2004

Genetic algorithms have been successfully applied to various optimization problems belonging to NP-hard problems. The sequential ordering problems(SOP) and the job shop scheduling problems(JSP) are well-known NP-hard problems with strong influence on industrial applications. Both problems share some common properties in that they have some imposed precedence constraints. When genetic algorithms are applied to this kind of problems, it is desirable for genetic operators to be designed to produce chromosomes satisfying the imposed precedence constraints. Several genetic operators applicable to such problems have been proposed. We call such genetic operators precedence-preserving genetic operators. This paper presents three existing precedence-preserving genetic operators: Precedence -Preserving Crossover(PPX), Precedence-preserving Order-based Crossover (POX), and Maximum Partial Order! Arbitrary Insertion (MPO/AI). In addition, it proposes two new operators named Precedence-Preserving Edge Recombination (PPER) and Multiple Selection Precedence-preserving Order-based Crossover (MSPOX) applicable to such problems. It compares the performance of these genetic operators for SOP and JSP in the perspective of their solution quality and execution time.

• The Korean Journal of Franchise Management
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• v.10 no.1
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• pp.19-32
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• 2019

Purpose - Since the opening of Korea's distribution market, the domestic network marketing market has been continuing to grow. In this context, research on network marketing independent operators, which plays the most important role in the network marketing industry, is insufficient. This study was to identify the effects of Independent Operator's Company Selection Attributions on the Economic and Non-Economic Satisfaction, Trust, and Recommendation. The results will provide strategic direction, theoretical and practical implications for companies and operators in the network marketing industry. Research design, data, and methodology - In order to verify the research hypotheses, the data were collected from Independent Operators of Network marketing industry using questionnaires. The pretest was conducted from January 8 to 19, 2018, and the main survey was conducted from February 1 to 28. A total of 210 questionnaires, of which 193 copies were collected. The data were analyzed with SPSS 21.0. and AMOS 21.0. Results - The results are as follows; product competitiveness and system competitiveness have significant effects on economic satisfaction and non-economic satisfaction. Economic and non-economic satisfaction have significant effects on business trust. Economic and non-economic satisfaction did not influence recommendation intention directly, but influence it indirectly. Business trust has a significant effect on business recommendation intention. Conclusions - After starting network marketing business as an independent operator, the competitiveness of the company is meaningless, and product competitiveness and system competitiveness are important factors for economic and non-economic satisfaction. Therefore, network marketing companies and independent operators should prioritize product competitiveness and system competitiveness between business development. The findings show that trust in the business is very important for active business Recommendation to others. Therefore, network marketing firms and independent operators need to make efforts to meet economic and non-economic satisfaction, which have a significant impact on business trust.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.12
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• pp.1210-1218
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• 2011

GA (Genetic Algorithms) are efficient for searching for global optima but may have some problems such as premature convergence, convergence to local extremum and divergence. These phenomena are related to the evolutionary operators. As population diversity converges to low value, the search ability of a GA decreases and premature convergence or converging to local extremum may occur but population diversity converges to high value, then genetic algorithm may diverge. To guarantee that genetic algorithms converge to the global optima, the genetic operators should be chosen properly. In this paper, we analyze the effects of the selection operator, crossover operator, and mutation operator on convergence properties, and propose the sweeping method of mutation probability and elitist propagation rate to maintain the diversity of the GA's population for getting out of the premature convergence. Results of simulation studies verify the feasibility of using these sweeping operators to avoid premature convergence and convergence to local extrema.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1521-1524
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• 2003

In this paper, we propose a "Distance Correlation Selection operator (DCS)" as a new selection operator. For Genetic Algorithm (GA), many improvements have been proposed. The MGG (Minimal Generation Gap) model proposed by Satoh et.al. shows good performance. The MGG model has all advantages of conventional models and the ability of avoiding the premature convergence and suppressing the evolutionary stagnation. The proposed method is an extension of selection operator in the original MGG model. Generally, GA has two types of selection operators, one is "selection for reproduction", and the other is "selection for survival"; the former is for crossover and the latter is the individuals which survive to the next generation. The proposed method is an extension of the former. The proposed method utilizes distance information between individuals. From this extension, the proposed method aims to expand a search area and improve ability to search solution. The performance of the proposed method is examined with several standard test functions. The experimental results show good performance better than the original MGG model.

• Journal of Navigation and Port Research
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• v.30 no.3 s.109
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• pp.219-226
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• 2006

To correspond actively to international economy, shipping and port environment change, world main ports have converged in competitiveness raising. However, existing researches have been intensively analyzed port competitiveness on among ports. So, this study analyzes the relations between the main factors of port selection and port competition players: central government, port authority, terminal operators, shipping companies, etc. This paper has a purpose that each port competition player makes a competitive strategy in accordance with this study. First, this study reviewed shipping and port market's environment change and port selection decision factors to correspond to these environment changes and on the basis of this review analyzed relativity between component port competition players and port competition factors. However, port authorities and terminal operators appeared high relevance about in side of expense, service, facilities etc. Because port authorities offered incentive to pull many shipping companies to their ports and terminal operators managed port authorities' ports. But we could deduce high relevance according to other market players' properties without port authorities and terminal operators. Port marketing strategy establishment among port competition players is available on the basis of these factors.