• Steel and Composite Structures
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• v.15 no.4
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• pp.451-466
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• 2013

This paper deals with the multi-objective optimization of tire reinforcement structures such as the tread belt and the carcass path. The multi-objective functions are defined in terms of the discrete-type design variables and approximated by artificial neutral network, and the sensitivity analyses of these functions are replaced with the iterative genetic evolution. The multi-objective optimization algorithm introduced in this paper is not only highly CPU-time-efficient but it can also be applicable to other multi-objective optimization problems in which the objective function, the design variables and the constraints are not continuous but discrete. Through the illustrative numerical experiments, the fiber-reinforced tire belt structure is optimally tailored. The proposed multi-objective optimization algorithm is not limited to the tire reinforcement structure, but it can be applicable to the generalized multi-objective structural optimization problems in various engineering applications.

• Journal of the Korean Operations Research and Management Science Society
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• v.18 no.3
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• pp.113-127
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• 1993

In this study, a substitution model of the evolutionary generations of technological products is presented. The purpose of the model is to examine the demand side mechanisms which generate successive product life cycles along the path of technological improvements. In the model, the nature of substitution processes is summarized dto the demand function which is derived from the consumer's udtility maximization problem. To describe the nature of technological substitution processes, the concept of the vertical differentiation and the consumption externalities are considered in the utility function. The former is used to characterize the result of technological improvement and the latter is used in explaining the inertia of demand. To show the validity of the model, an empirical study is carried out using the data of the world DRAM market.

• Journal of Korea Game Society
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• v.17 no.5
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• pp.123-132
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• 2017

The path-finding algorithm refers to an algorithm for navigating the route order from the current position to the destination in a virtual world in a game. The conventional path-finding algorithm performs graph search based on cost such as A-Star and Dijkstra. A-Star and Dijkstra require movable node and edge data in the world map, so it is difficult to apply online games with lots of map data. In this paper, we provide a Heuristic-based Genetic Algorithm Path-finding(HGAP) using Genetic Algorithm(GA). Genetic Algorithm is a path-finding algorithm applicable to game with variable environment and lots of map data. It seek solutions through mating, crossing, mutation and evolutionary operations without the map data. The proposed algorithm is based on Binary-Coded Genetic Algorithm and searches for a path by performing a heuristic operation that estimates a path to a destination to arrive at a destination more quickly.

• Journal of Korea Game Society
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• v.11 no.2
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• pp.57-68
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• 2011

This study approaches how newly emerged game companies has implemented strategies for product diversification according to market growth cycle(beginninggrowing-mature) by empirical case study through evolutionary theory and resource based theory approach. At the beginning, online game companies had grown with different strategies(technology based, service based) by initial condition(genre, technological level, user attribute). After market growth, for product diversification, these companies carried out path-dependent alliance strategy(complementary, competitive) depending on resource base(technology capacity, service capacity based). As online game market getting mature, these companies has adapted flexibly in responding to market growth cycle by integrated strategy(naturally selected to mobilize every possible resource capability). By analyzing the alliance strategies pattern of online game companies in newly emerged game industry according to market growth cycle through combination of resource based theory and evolutionary theory, these results suggest that new industrial, theoretical, policy model is required.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.24 no.4
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• pp.441-447
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• 2015

This paper proposes a novel fuzzy-based multi-criteria decision making method and implements a footstep planner for humanoid robots with it. Humanoid robots require additional footstep planning process in addition to path planning for the autonomous navigation. Moreover, it is necessary to consider safety and energy consumption as well as path efficiency and multi-criteria decision making is indispensable. The proposed method can provide not only well- distributed and non-dominated, but also more preferable solutions for users. The planned footsteps by the proposed method were verified through simulation. The results indicate that the user's preference is properly reflected in optimized solutions maintaining solution quality.

• Journal of the Korean association of regional geographers
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• v.18 no.3
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• pp.283-297
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• 2012

This study aims to analyze an evolutionary path and the dynamics of the Seoul Digital Industrial Complex in Korea based on the analysis of cluster life cycles. From the mid 1960s to the late 1990s, the life cycles and their characteristics of the Seoul Digital Industrial Complex (Guro Industrial Park) are examined as emergence-growth-sustainment-decline focused on the number of firms and employees. After the late 1990s, the number of firms and employees increases rapidly and the active actors of the growth and restructuring are transformed to the technology-intensive SMEs and knowledge-based service firms. Knowledge industry centers (apartment-type factories) help evolve into the life cycle of transformation as knowledge-based clusters after the mid 2000s.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.17 no.1
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• pp.83-91
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• 2004

Nonlinear system responses of an impact system under randomly perturbed harmonic excitations are predicted in the probability domain by adopting the semi-analytical procedure previously developed. The semi-analytical procedure is obtained by solving the Fokker-Planck equation corresponding to the stochastic differential equation of the given impact system by utilizing the path-integral solution. The evolutionary joint probability density functions are generated by using the method, and the characteristics of nonlinear dynamic response behaviors of the system are examined. Noise effects on the responses are also examined. It Is found that the semi-analytical method can provides the accurate information of the responses via the joint probability functions for the impact system. It is found that the noises weaken and eventually terminate the chaos in the responses, but it is also found that the chaotic signatures reside in the presence of the external noise with relatively high intensity. The joint probability density function shows that the ensemble of the system responses are weakly stationary.

• Journal of the Korean Society for Railway
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• v.19 no.3
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• pp.388-396
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• 2016

The metropolitan subway network of Seoul has gone through many evolutionary processes in past decades to disperse the floating population and improve the traffic flow. In this study, we analyzed how the structural characteristics and the efficiency of the subway network have changed according to the dynamic evolutionary processes of the metropolitan subway network of Seoul. We have also proposed new measures that can be used to characterize the structural properties of the subway network more practically. It is shown that the global efficiency is about 74%, which is higher than those of subway networks of foreign countries. It should also be considered that passenger flow between stations is even higher, at about 85%. Since the private lines, including line 9, the New Bundang line, the Uijeongbu line, and the Ever line do not release their traffic data since September, 2013, only 5 years of data from September, 2008 to September, 2013 is available. So, in this study we limit the analysis period to these 5 years.

• The Transactions of the Korea Information Processing Society
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• v.5 no.3
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• pp.671-680
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• 1998

Network services, such as teleconferencing, remote diagnostics and education, and CSCW require multicasting. Multicast routing methods can be divided into two categories. One is the shortest path tree method and the other is the minimal Steiner tree method. The latter has an advantage over the former in that only one Steiner tree is needed for a group. However, finding a minimal Steiner tree is an NP-complete problem and it is necessary to find an efficient heuristic algorithm. In this paper, we present an evolutionary optimization method for finding minimal Steiner trees without sacrificing too much computational efforts. In particular, we describe a tree-based genetic encoding scheme which is in sharp constast with binary string representations usually adopted in convetional genetic algorithms. Experiments have been performed to show that the presented method can find optimal Steiner trees for given vetwork configurations. Comparitivie studies have shown that the evolutionary method finds on average a better solution than other conventional heustric algorithms.

• Journal of Korean Society of Transportation
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• v.32 no.5
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• pp.554-566
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• 2014

An objective of VMS(Variable Message Signs) is to make transportation system effective specifically for driver's path selection. The traffic solutions including a VMS problem can be modeled through Game Theory, however, the majority of the studies can not model various driver's response according to VMS information in game theory. So, this paper tries to analyze a driver's response according to VMS traffic informations through evolutionary game theory. We apply a behavior characteristics of driver to evolutionary game theory, then finds drivers are only accepting in case of the biggest pay-off, and if a traffic flow finds a balance over time, ratio of accepting information is converged as an evolutionary stable state gradually. Consequently, the strategy of the other drivers such as traffic problems can not be predicted accurately. In case, drivers repeat between groups and reasonable judgment by the experience, we expect that VMS can provide strategic information through evolutionary game theory.