• 제목/요약/키워드: Evolution strategy

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Purposes, Results, and Types of Software Post Life Cycle Changes

  • Koh, Seokha;Han, Man Pil
    • Journal of Information Technology Applications and Management
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    • 제22권3호
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    • pp.143-167
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    • 2015
  • This paper addresses the issue how the total life cycle cost may be minimized and how the cost should be allocated to the acquirer and developer. This paper differentiates post life cycle change (PLCC) endeavors from PLCC activities, rigorously classifies PLCC endeavors according to the result of PLCC endeavors, and rigorously defines the life cycle cost of a software product. This paper reviews classical definitions of software 'maintenance' types and proposes a new typology of PLCC activities too. The proposed classification schemes are exhaustive and mutually exclusive, and provide a new paradigm to review existing literatures regarding software cost estimation, software 'maintenance,' software evolution, and software architecture from a new perspective. This paper argues that the long-term interest of the acquirer is not protected properly because warranty period is typically too short and because the main concern of warranty service is given to removing the defects detected easily. Based on the observation that defects are caused solely by errors the developer has committed for software while defects are often induced by using for hardware (so, this paper cautiously proposes not to use the term 'maintenance' at all for software), this paper argues that the cost to remove defects should not be borne by the acquirer for software.

다목적을 갖는 혼합모델 조립라인의 밸런싱과 투입순서를 위한 공생 진화알고리즘 (A Symbiotic Evolutionary Algorithm for Balancing and Sequencing Mixed Model Assembly Lines with Multiple Objectives)

  • 김여근;이상선
    • 한국경영과학회지
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    • 제35권3호
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    • pp.25-43
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    • 2010
  • We consider a multi-objective balancing and sequencing problem in mixed model assembly lines, which is important for an efficient use of the assembly lines. In this paper, we present a neighborhood symbiotic evolutionary algorithm to simultaneously solve the two problems of balancing and model sequencing under multiple objectives. We aim to find a set of well-distributed solutions close to the true Pareto optimal solutions for decision makers. The proposed algorithm has a two-leveled structure. At Level 1, two populations are operated : One consists of individuals each of which represents a partial solution to the balancing problem and the other consists of individuals for the sequencing problem. Level 2, which is an upper level, works one population whose individuals represent the combined entire solutions to the two problems. The process of Level 1 imitates a neighborhood symbiotic evolution and that of Level 2 simulates an endosymbiotic evolution together with an elitist strategy to promote the capability of solution search. The performance of the proposed algorithm is compared with those of the existing algorithms in convergence, diversity and computation time of nondominated solutions. The experimental results show that the proposed algorithm is superior to the compared algorithms in all the three performance measures.

보 보강재 배치 최적화 문제에서의 기하구속조건 처리기법 (A Geometry Constraint Handling Technique in Beam Stiffener Layout Optimization Problem)

  • 이준호;박영진;박윤식
    • 한국소음진동공학회:학술대회논문집
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    • 한국소음진동공학회 2004년도 춘계학술대회논문집
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    • pp.870-875
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    • 2004
  • Beam stiffeners have frequently been used for raising natural frequencies of base structures. In stiffener layout optimization problems, most of the previous researches considering the position and/or the length of the stiffener as design variables dealt with structures having just simple convex shapes such as a square or rectangle. The reason is concave shape structures have difficulties ill formulating geometry constraints. In this paper, a new geometry constraint handling technique, which can define both convex and concave feasible lesions and measure a degree of geometry constraint violation, is proposed. Evolution strategies (ESs) is utilized as an optimization tool. In addition, the constraint-handling technique of EVOSLINOC (EVOlution Strategy for scalar optimization with Lineal and Nonlinear Constraints) is utilized to solve constrained optimization problems. From a numerical example, the proposed geometry constraint handling technique is verified and proves that the technique can easily be applied to structures in net only convex but also concave shapes, even with a protrusion or interior holes.

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Organizational Behavior of Established Firms to a Disruptive Innovation : The Case of NEC's Behavior in the Japanese Laptop Computer Industry

  • Wi Jong-Hyun
    • 기술혁신연구
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    • 제14권2호
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    • pp.29-48
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    • 2006
  • This paper analyzes organizational behavior of an established firm when disruptive innovation, a change in product architecture, occurs on a previous product. For the analysis, the paper analyzes and compares the behavior of an established fm through product trajectories between NEC (an established firm) and Toshiba (a new entrance) in the Japanese laptop computers industry. An established firm that has developed and produced a previous product is difficult in adapting to a disruptive innovation due to accumulated immense knowledge through a previous product. By using regression model in the product trajectory analysis, the paper analyzes the behavior of established firms. Product trajectory means a pattern of product strategy shown in a series of products. Two facts found in the paper are as follows. First, though NEC was able to develop a laptop computer at the same time with Toshiba, it was restricted by the resources of a previous product in the early stage. Second, possibility of teaming trap in the adapting process was found. The paper found the risk that too much commitment in one evolution stage would prohibit the adapting behavior in the next evolution stage.

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Post-reionization Kinetic Sunyaev-Zel'dovich Effect in Illustris Simulation

  • Park, Hyunbae;Sabiu, Cristiano;Li, Xiao-dong;Park, Changbom;Kim, Juhan
    • 천문학회보
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    • 제42권1호
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    • pp.52.2-53
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    • 2017
  • We develop a methodology to use the redshift dependence of the galaxy 2-point correlation function (2pCF) as a probe of cosmological parameters. The positions of galaxies in comoving Cartesian space varies under different cosmological parameter choices, inducing a redshift-dependent scaling in the galaxy distribution. This geometrical distortion can be observed as a redshift-dependent rescaling in the measured 2pCF. The shape of the 2pCF exhibits a significant redshift evolution when the galaxy sample is analyzed under a cosmology differing from the true, simulated one. Other contributions, including the gravitational growth of structure, galaxy bias, and the redshift space distortions, do not produce large redshift evolution in the shape. We show that one can make use of this geometrical distortion to constrain the values of cosmological parameters governing the expansion history of the universe. This method could be applicable to future large scale structure surveys, especially photometric surveys such as DES, LSST, to derive tight cosmological constraints. This work is a continuation of our previous works as a strategy to constrain cosmological parameters using redshift-invariant physical quantities.

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Multi-Objective Handover in LTE Macro/Femto-Cell Networks

  • Roy, Abhishek;Shin, Jitae;Saxena, Navrati
    • Journal of Communications and Networks
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    • 제14권5호
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    • pp.578-587
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    • 2012
  • One of the key elements in the emerging, packet-based long term evolution (LTE) cellular systems is the deployment of multiple femtocells for the improvement of coverage and data rate. However, arbitrary overlaps in the coverage of these femtocells make the handover operation more complex and challenging. As the existing handover strategy of LTE systems considers only carrier to interference plus noise ratio (CINR), it often suffers from resource constraints in the target femtocell, thereby leading to handover failure. In this paper, we propose a new efficient, multi-objective handover solution for LTE cellular systems. The proposed solution considers multiple parameters like signal strength and available bandwidth in the selection of the optimal target cell. This results in a significant increase in the handover success rate, thereby reducing the blocking of handover and new sessions. The overall handover process is modeled and analyzed by a three-dimensional Markov chain. The analytical results for the major performance metrics closely resemble the simulation results. The simulation results show that the proposed multi-objective handover offers considerable improvement in the session blocking rates, session queuing delay, handover latency, and goodput during handover.

A Context-aware Task Offloading Scheme in Collaborative Vehicular Edge Computing Systems

  • Jin, Zilong;Zhang, Chengbo;Zhao, Guanzhe;Jin, Yuanfeng;Zhang, Lejun
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제15권2호
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    • pp.383-403
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    • 2021
  • With the development of mobile edge computing (MEC), some late-model application technologies, such as self-driving, augmented reality (AR) and traffic perception, emerge as the times require. Nevertheless, the high-latency and low-reliability of the traditional cloud computing solutions are difficult to meet the requirement of growing smart cars (SCs) with computing-intensive applications. Hence, this paper studies an efficient offloading decision and resource allocation scheme in collaborative vehicular edge computing networks with multiple SCs and multiple MEC servers to reduce latency. To solve this problem with effect, we propose a context-aware offloading strategy based on differential evolution algorithm (DE) by considering vehicle mobility, roadside units (RSUs) coverage, vehicle priority. On this basis, an autoregressive integrated moving average (ARIMA) model is employed to predict idle computing resources according to the base station traffic in different periods. Simulation results demonstrate that the practical performance of the context-aware vehicular task offloading (CAVTO) optimization scheme could reduce the system delay significantly.

The Evolution of Korea's Basic Acts on Science and Technology and their Characteristics

  • Lee, Changyul;Lee, Elly Hyanghee;Kim, Seongsoo
    • Asian Journal of Innovation and Policy
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    • 제10권3호
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    • pp.355-379
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    • 2021
  • This study examined the evolution of S&T Basic Acts in Korea from the Science and Technology Promotion Act (1967) through the Special Act on STI (1997) to the Framework Act on Science and Technology (2001) in the following aspects: 1) comprehensive plans, 2) coordination mechanisms for S&T policies, 3) enforcement of R&D programs and performance diffusion, 4) promotion of human resources, 5) and S&T investment and budgeting. Before the Framework Act on S&T was enacted in 2001, critical issues were found in establishing S&T master plans, promotion of R&D programs, comprehensive coordination mechanisms, and R&D budgeting. The three Basic Acts have expanded the scope of regulation over time to cover the entire cycle of the S&T process. They concern a wide range of issues, including creating a basis for scientific and technological development, S&T promotion, disseminating and commercializing research outcomes, and preventing adverse effects from science and technology. The content of the Basic Acts has evolved in response to changes in the political, economic, and social environment of Korean industry during the past five decades.

비즈니스 모델의 진화: 플러그에서 플랫폼으로 -다원 DNS IoT 기술의 사례- (Evolution of Business Model: From Plug To Platform - Dawon DNS Business Case-)

  • 박민혁;여운남;이정우
    • 한국IT서비스학회지
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    • 제20권5호
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    • pp.105-118
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    • 2021
  • As we enter the era of the 4th industrial revolution, information and communication technologies, including artificial intelligence and big data, are converging throughout society. Especially, as the importance of the social foundation of hyper-connection grows, the social influence of IoT, a network of connecting objects, people, and various entities, is also gradually expanding. In addition, as a pandemic, COVID-19, continues, interests in untact-oriented technology and service development are growing more than ever, and each company is trying to establish a core competency strategy to gain an edge in competition in the changing society. This study is a case study centered on Dawon DNS, a company that provides an IoT-based AI smart plug platform. Dawon DNS is broadening its services while developing products by applying advanced technologies, and this study is aiming to investigate the core competencies of the business evolution process. The obtained result of this study will provide implications for companies to become more competitive by suggesting the attitudes and strategies that startups should have during the transforming business environment.

Knee-driven many-objective sine-cosine algorithm

  • Hongxia, Zhao;Yongjie, Wang;Maolin, Li
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제17권2호
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    • pp.335-352
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    • 2023
  • When solving multi-objective optimization problems, the blindness of the evolution direction of the population gradually emerges with the increase in the number of objectives, and there are also problems of convergence and diversity that are difficult to balance. The many- objective optimization problem makes some classic multi-objective optimization algorithms face challenges due to the huge objective space. The sine cosine algorithm is a new type of natural simulation optimization algorithm, which uses the sine and cosine mathematical model to solve the optimization problem. In this paper, a knee-driven many-objective sine-cosine algorithm (MaSCA-KD) is proposed. First, the Latin hypercube population initialization strategy is used to generate the initial population, in order to ensure that the population is evenly distributed in the decision space. Secondly, special points in the population, such as nadir point and knee points, are adopted to increase selection pressure and guide population evolution. In the process of environmental selection, the diversity of the population is promoted through diversity criteria. Through the above strategies, the balance of population convergence and diversity is achieved. Experimental research on the WFG series of benchmark problems shows that the MaSCA-KD algorithm has a certain degree of competitiveness compared with the existing algorithms. The algorithm has good performance and can be used as an alternative tool for many-objective optimization problems.