• 제목/요약/키워드: objective performance

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A Many-objective Particle Swarm Optimization Algorithm Based on Multiple Criteria for Hybrid Recommendation System

  • Hu, Zhaomin;Lan, Yang;Zhang, Zhixia;Cai, Xingjuan
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제15권2호
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    • pp.442-460
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    • 2021
  • Nowadays, recommendation systems (RSs) are applied to all aspects of online life. In order to overcome the problem that individuals who do not meet the constraints need to be regenerated when the many-objective evolutionary algorithm (MaOEA) solves the hybrid recommendation model, this paper proposes a many-objective particle swarm optimization algorithm based on multiple criteria (MaPSO-MC). A generation-based fitness evaluation strategy with diversity enhancement (GBFE-DE) and ISDE+ are coupled to comprehensively evaluate individual performance. At the same time, according to the characteristics of the model, the regional optimization has an impact on the individual update, and a many-objective evolutionary strategy based on bacterial foraging (MaBF) is used to improve the algorithm search speed. Experimental results prove that this algorithm has excellent convergence and diversity, and can produce accurate, diverse, novel and high coverage recommendations when solving recommendation models.

백내장 환자에서 비구면 다초점 인공수정체 삽입 후 시기능 평가 (Evaluation of Visual Performance for Implanted Aspheric Multifocal Intraocular Lens in the Cataract Patients)

  • 김재윤;이군자
    • 한국안광학회지
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    • 제18권3호
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    • pp.347-356
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    • 2013
  • 목적: 비구면 다초점 인공수정체인 ReSTOR$^{(R)}$ SN6AD3 삽입안의 시력과 시기능 변화를 분석하였다. 방법: 양안 또는 단안에 비구면 다초점 인공수정체(ReSTOR$^{(R)}$ SN6AD3)를 삽입한 백내장 환자 19명의 30안을 대상으로 하였다. 수술 전, 수술 후 1주일, 1개월 및 3개월 후에 시력과 객관적인 시기능을 측정하였고 수술 3개월 후 인공수정체 삽입안의 시기능 측정값을 동일 연령대의 정상안 20명(38안)과 비교하였다. 원거리 시력은 2 m 거리에서 LCD chart ETDRS 시력표를 이용하여 측정하였고, 중간거리(50 cm)과 근거리(30 cm) 시력은 Jaeger chart를 이용하였다. 객관적인 시기능은 OQAS 장비를 이용하여 OSI (objective scatter index, 객관적 산란지수), MTF (modulation transfer function, 변조전달함수) cut off, Strehl ratio를 4 mm 동공크기에서 측정하여 수술 후 경과기간에 따른 측정값을 비교 평가하였다. 수술 3개월 째 시력 및 시기능은 객관적 평가와 주관적인 평가를 통해 동일 연령대의 정상안과 비교하였다. 결과: 나안 원거리 시력과 OSI, MTF와 Strehl ratio는 다초점 인공수정체 삽입 1개월까지 유의하게 향상되었다(p<0.05). 수술 3개월 후 다초점 인공수정체 삽입안의 MTF와 Strehl ratio는 정상 대조군의 수준으로 회복되었지만, OSI는 대조군보다 높은 값으로 측정되었다(p<0.001). 자각적인 원거리 및 근거리 시력에 대한 만족도는 높았지만, 중간거리 시력에 대한 만족도가 낮으며 눈부심과 빛 번짐 증상이 나타났다. 결론: 비구면 다초점 인공수정체 삽입안의 시기능은 수술 1개월 후부터 안정화되며 동일 연령대의 정상안의 수준으로 개선되지만 만족스러운 중간거리 시력을 제공하지 못하며 눈부심과 빛 번짐의 시각적 불편감이 나타나는 것으로 사료된다.

다목적 시뮬레이션 통합 하이브리드 유전자 알고리즘을 사용한 수동 조립라인의 동기 작업 모델 (A Synchronized Job Assignment Model for Manual Assembly Lines Using Multi-Objective Simulation Integrated Hybrid Genetic Algorithm (MO-SHGA))

  • 무하마드 임란;강창욱
    • 산업경영시스템학회지
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    • 제40권4호
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    • pp.211-220
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    • 2017
  • The application of the theoretical model to real assembly lines has been one of the biggest challenges for researchers and industrial engineers. There should be some realistic approach to achieve the conflicting objectives on real systems. Therefore, in this paper, a model is developed to synchronize a real system (A discrete event simulation model) with a theoretical model (An optimization model). This synchronization will enable the realistic optimization of systems. A job assignment model of the assembly line is formulated for the evaluation of proposed realistic optimization to achieve multiple conflicting objectives. The objectives, fluctuation in cycle time, throughput, labor cost, energy cost, teamwork and deviation in the skill level of operators have been modeled mathematically. To solve the formulated mathematical model, a multi-objective simulation integrated hybrid genetic algorithm (MO-SHGA) is proposed. In MO-SHGA each individual in each population acts as an input scenario of simulation. Also, it is very difficult to assign weights to the objective function in the traditional multi-objective GA because of pareto fronts. Therefore, we have proposed a probabilistic based linearization and multi-objective to single objective conversion method at population evolution phase. The performance of MO-SHGA is evaluated with the standard multi-objective genetic algorithm (MO-GA) with both deterministic and stochastic data settings. A case study of the goalkeeping gloves assembly line is also presented as a numerical example which is solved using MO-SHGA and MO-GA. The proposed research is useful for the development of synchronized human based assembly lines for real time monitoring, optimization, and control.

A Bi-objective Game-based Task Scheduling Method in Cloud Computing Environment

  • Guo, Wanwan;Zhao, Mengkai;Cui, Zhihua;Xie, Liping
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제16권11호
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    • pp.3565-3583
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    • 2022
  • The task scheduling problem has received a lot of attention in recent years as a crucial area for research in the cloud environment. However, due to the difference in objectives considered by service providers and users, it has become a major challenge to resolve the conflicting interests of service providers and users while both can still take into account their respective objectives. Therefore, the task scheduling problem as a bi-objective game problem is formulated first, and then a task scheduling model based on the bi-objective game (TSBOG) is constructed. In this model, energy consumption and resource utilization, which are of concern to the service provider, and cost and task completion rate, which are of concern to the user, are calculated simultaneously. Furthermore, a many-objective evolutionary algorithm based on a partitioned collaborative selection strategy (MaOEA-PCS) has been developed to solve the TSBOG. The MaOEA-PCS can find a balance between population convergence and diversity by partitioning the objective space and selecting the best converging individuals from each region into the next generation. To balance the players' multiple objectives, a crossover and mutation operator based on dynamic games is proposed and applied to MaPEA-PCS as a player's strategy update mechanism. Finally, through a series of experiments, not only the effectiveness of the model compared to a normal many-objective model is demonstrated, but also the performance of MaOEA-PCS and the validity of DGame.

셀 제조시스템의 핵심성공요인, 수용태도, 성과간의 관련성에 관한 연구 (Linking Critical Success Factors, Implementation Attitudes and Performance of Cellular Manufacturing Systems)

  • 육근효
    • 경영과학
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    • 제18권1호
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    • pp.89-105
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    • 2001
  • The performance of Cellular Manufacturing (CM) systems has been rigorously investigated during the last two decades, but the extent of empirical research on CM is limited. A major objective of this study is to examine the relationship between critical success factors, employees' implementation attitudes and performance of CM systems. Two hypothesis were formulated &d Tested: (1) The impact of critical success factors on performance and to what extent does certain critical success factors correlate with performance\ulcorner (2) How does the relationship between critical success factors and performance differ by employees' implementation attitudes\ulcorner Results from the study provide partial support for relationship between critical success factors (infrastructure, organizational immersion, autonomous management) and performance. The results also show that differences in performance of organizations grouped by degree of employees' attitudes could be found.

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THE STUDY OF MULI-LEVEL PERFORMANCE MEASUREMENT APPROACH FOR VALUE MANAGEMENT OF CIVIL INFRASTRUCTURE PROJECTS

  • Jong-Kwon Lim;Min-Jae Lee;Dong-Youl Lee
    • 국제학술발표논문집
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    • The 3th International Conference on Construction Engineering and Project Management
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    • pp.1294-1299
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    • 2009
  • Best value in value engineering has relation to cost and performance. But a severe problem in VE study of a project is to reduce value due to loss of performance, caused by focusing on cost reduction. Also a lack of understanding performance concept, no trial VE workshop as well as cost saving-based policy have not satisfied customer needs. A efficient and practical methodology for accomplishing best value in construction projects is proposed. This study developed a more objective approach for performance measurement approach of mega projects and suggested a systematic process of performance quantitative analysis verifying value improvement. The proposed performance measurement method would be very useful for better communication and consensus between stakeholders and VE team especially through value engineering.

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Sparse and low-rank feature selection for multi-label learning

  • Lim, Hyunki
    • 한국컴퓨터정보학회논문지
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    • 제26권7호
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    • pp.1-7
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    • 2021
  • 본 논문에서는 다중 레이블 분류를 위한 특징 선별 기법을 제안한다. 기존 많은 특징 선별 기법들은 상호정보척도 등을 이용하여 특징과 레이블 사이의 연관성을 계산하여 특징을 선별하였다. 하지만 상호정보척도는 결합 확률을 요구하기 때문에 실제 전제 특징 집합에서 결합 확률을 계산하는 것은 어렵다. 따라서 소수의 특징만 계산이 가능하여 지역적 최적화만 가능하다는 단점을 가진다. 이런 지역적 최적화 문제를 피해, 주어진 특징 전체 공간에서 저랭크 공간을 구성하고, 희소성을 가진 특징들을 선별할 수 있는 특징 선별 기법을 제안한다. 이를 위해 뉴클리어 노름을 이용해 회귀 기반의 목적함수를 설계하였고, 이 목적 함수의 최적화 문제를 풀기 위한 경사하강법 방식의 알고리즘을 제안하였다. 4가지의 데이터와 3가지 다중 레이블 분류 성능을 기준으로 다중 레이블 분류 실험 결과를 통해 제안하는 방법론이 기존 특징 선별 기법보다 좋은 성능을 나타내는 것을 보였다. 또한 제안하는 목적함수의 파라미터 값 변화에도 성능 변화가 둔감한 것을 실험적인 결과로 확인하였다.

선호도기반 최적화방법을 이용한 교량의 유지보수계획 (Maintenance Planning for Deteriorating Bridge using Preference-based Optimization Method)

  • 이선영;고현무;박원석;김현중
    • 대한토목학회논문집
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    • 제28권2A호
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    • pp.223-231
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    • 2008
  • 이 논문에서는 교량의 유지보수비용을 최소화할 뿐만 아니라 교량의 성능을 동시에 최대화할 수 있는 새로운 유지보수계획법을 제시한다. 교량 수명연한 동안의 유지보수비용과 교량의 바닥판, 주형, 하부구조의 상태등급으로 표현되는 교량의 성능을 동시에 최적화 하는 다목적 최적화 문제를 구성하여 최적의 유지보수계획을 수립한다. 다목적 최적화문제의 해를 얻기 위한 수치해석 방법으로 유전자 알고리즘(Genetic Algorithm, GA)을 사용하고, 다목적 최적화방법을 적용하여 얻어진 여러 개의 해집합 중 최적해의 선택을 위한 의사결정(decision making)을 위해 선호도기반 최적화방법을 적용한다. 일반적인 5경간의 PSC I형 교량에 대한 수치예제를 통해, 이 연구에서 제안하는 방법이 유지보수비용 및 교량성능간의 균형 있는 최적화를 이룰 수 있음을 보인다.

구배 지수에 근거한 MEMS 구조물의 강건 최적 설계 기법 (Gradient Index Based Robust Optimal Design Method for MEMS Structures)

  • 한정삼;곽병만
    • 대한기계학회논문집A
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    • 제27권7호
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    • pp.1234-1242
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    • 2003
  • In this paper we present a simple and efficient robust optimal design formulation for MEMS structures and its application to a resonant-type micro probe. The basic idea is to use the gradient index (GI) to improve robustness of the objective and constraint functions. In the robust optimal design procedure, a deterministic optimization for performance of MEMS structures is followed by design sensitivity analysis with respect to uncertainties such as fabrication errors and change of operating conditions. During the process of deterministic optimization and sensitivity analysis, dominant performance and uncertain variables are identified to define GI. The GI is incorporated as a term of objective and constraint functions in the robust optimal design formulation to make both performance and robustness improved. While most previous approaches for robust optimal design require statistical information on design variations, the proposed GI based method needs no such information and therefore is cost-effective and easily applicable to early design stages. For the micro probe example, robust optimums are obtained to satisfy the targets for the measurement sensitivity and they are compared in terms of robustness and production yield with the deterministic optimums through the Monte Carlo simulation. This method, although shown for MEMS structures, may as well be easily applied to conventional mechanical structures where information on uncertainties is lacking but robustness is highly important.

구배 지수에 근거한 강건 최적 설계 기법을 이용한 공진형 미소탐침의 강건 최적화 (Robust Optimization of a Resonant-type Micro-probe Using Gradient Index Based Robust Optimal Design Method)

  • 한정삼;곽병만
    • 대한기계학회:학술대회논문집
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    • 대한기계학회 2003년도 춘계학술대회
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    • pp.1254-1261
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    • 2003
  • In this paper we present a simple and efficient robust optimal design formulation and its application to a resonant-type micro probe. The basic idea is to use the Gradient Index (GI) to improve robustness of the objective and constraint functions. In the robust optimal design procedure, a deterministic optimization for performance of MEMS structures is followed by design sensitivity analysis with respect to uncertainties such as fabrication errors and change of operating conditions. During the process of deterministic optimization and sensitivity analysis, dominant performance and uncertain variables are identified to define GI. The GI is incorporated as a term of objective and constraint functions in the robust optimal design formulation to make both performance and robustness improved. While most previous approaches for robust optimal design require statistical information on design variations, the proposed GI based method needs no such information and therefore is cost-efficient and easily applicable to early design stages. For the micro probe example, robust optimums are obtained to satisfy the targets for the measurement sensitivity and they are compared in terms of robustness and production yield with the deterministic optimums through the Monte Carlo simulation.

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