• 제목/요약/키워드: Cost-based Objective

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추계학적 선형화 기법을 접목한 다목적 최적화기법에 의한 비선형 지진격리시스템의 최적설계 (Optimal design of nonlinear seismic isolation system by a multi-objective optimization technique integrated with a stochastic linearization method)

  • 곽신영;옥승용;고현무
    • 한국지진공학회논문집
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    • 제14권2호
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    • pp.1-13
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    • 2010
  • 본 논문에서는 비선형 지진격리교량의 최적 설계 방법을 제시하였다. 최적설계를 위한 목적함수로는 교각과 지진격리장치의 파괴확률을 고려하였으며, 상충하는 두 목적함수를 동시에 최적화하는 다수의 해를 효율적으로 검색하고자 유전자 알고리즘에 기반한 다목적 최적화기법을 도입하였다. 또한, 최적화 과정에서 요구되는 다수의 비선형 시간이력해석을 수행하지 않고도 교량의 확률적 응답을 효율적으로 예측할 수 있는 추계학적 선형화 방법을 접목하였다. 제시하는 방법의 효율성을 검증하기 위한 수치 예로서 실제 교량인 남한강교를 고려하였고, 제안하는 방법과 기존 비선형 시간이력해석을 이용한 생애주기비용 기반 설계법을 각각 적용하여 내진성능을 비교하였다. 내진성능을 비교한 결과, 제시하는 방법이 기존의 비용에 기반한 최적설계보다 우수한 성능 및 경제성을 보임을 검증하였다. 또한, 다양한 지진하중에 대해서도 제안된 방법이 보다 개선된 성능을 보임을 확인하였다.

구조BIM기반 공사비 상세분석 프로세스 구축 (Development of Construction Cost Analysis Process Based on Structural Building Information Modeling)

  • 이승일
    • 한국건축시공학회:학술대회논문집
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    • 한국건축시공학회 2012년도 추계 학술논문 발표대회
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    • pp.237-238
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    • 2012
  • As a way to improve productivity and integrated project delivery in construction industry, BIM(building Information Modeling) using IT technique is being studied and applied recently. S-BIM application Process was established that enable efficient work through Structural BIM detailed Model in consideration of the collaboration among relevant fields. This study has the objective applying S-BIM technique to enable effective Cost Analysis in initial design phase and presenting the method for practical works using Construction Cost Analysis Process based on S-BIM.

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ESGA를 이용한 불평형 배전계통의 커패시터 설치에 관한 연구 (A Study on Capacitor Placement Using ESGA Hybrid Approach in Unbalanced Distribution Systems)

  • 김규호;이유정;이상봉;유석구
    • 대한전기학회논문지:전력기술부문A
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    • 제52권6호
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    • pp.316-324
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    • 2003
  • This paper applied Elite-based Simplex-GA hybrid approach combined with Muptipop-GA (ESGA) to determining the location, size and number of capacitors to improve voltage profile and minimize power losses in unbalanced distribution systems. One of the main obstacles in applying GA to complex problems has been the high computational cost due to their slow convergence rate. To alleviate this difficulty, ESGA approach was developed that combines Elite-based Simplex-GA hybrid approach with Muptipop-GA. The objective function formulated consists of two terms: cost for energy losses and cost related to capacitor purchase and capacitor installation. The cost function associated with capacitor placement is considered as a step function due to banks of standard discrete capacities. Its efficiency was proved through the application in IEEE 13 bus and 34 bus test systems and was compared with several methods using GA.

A Multi-objective Optimization Approach to Workflow Scheduling in Clouds Considering Fault Recovery

  • Xu, Heyang;Yang, Bo;Qi, Weiwei;Ahene, Emmanuel
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제10권3호
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    • pp.976-995
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    • 2016
  • Workflow scheduling is one of the challenging problems in cloud computing, especially when service reliability is considered. To improve cloud service reliability, fault tolerance techniques such as fault recovery can be employed. Practically, fault recovery has impact on the performance of workflow scheduling. Such impact deserves detailed research. Only few research works on workflow scheduling consider fault recovery and its impact. In this paper, we investigate the problem of workflow scheduling in clouds, considering the probability that cloud resources may fail during execution. We formulate this problem as a multi-objective optimization model. The first optimization objective is to minimize the overall completion time and the second one is to minimize the overall execution cost. Based on the proposed optimization model, we develop a heuristic-based algorithm called Min-min based time and cost tradeoff (MTCT). We perform extensive simulations with four different real world scientific workflows to verify the validity of the proposed model and evaluate the performance of our algorithm. The results show that, as expected, fault recovery has significant impact on the two performance criteria, and the proposed MTCT algorithm is useful for real life workflow scheduling when both of the two optimization objectives are considered.

Genetic algorithms for balancing multiple variables in design practice

  • Kim, Bomin;Lee, Youngjin
    • Advances in Computational Design
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    • 제2권3호
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    • pp.241-256
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    • 2017
  • This paper introduces the process for Multi-objective Optimization Framework (MOF) which mediates multiple conflicting design targets. Even though the extensive researches have shown the benefits of optimization in engineering and design disciplines, most optimizations have been limited to the performance-related targets or the single-objective optimization which seek optimum solution within one design parameter. In design practice, however, designers should consider the multiple parameters whose resultant purposes are conflicting. The MOF is a BIM-integrated and simulation-based parametric workflow capable of optimizing the configuration of building components by using performance and non-performance driven measure to satisfy requirements including build programs, climate-based daylighting, occupant's experience, construction cost and etc. The MOF will generate, evaluate all different possible configurations within the predefined each parameter, present the most optimized set of solution, and then feed BIM environment to minimize data loss across software platform. This paper illustrates how Multi-objective optimization methodology can be utilized in design practice by integrating advanced simulation, optimization algorithm and BIM.

불확실성을 고려한 철도 교량의 LCC분석 시스템 개발 (Development of Uncertainty-Based Life-Cycle Cost System for Railroad Bridges)

  • 조중연;선종완;김이현;조효남
    • 한국철도학회:학술대회논문집
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    • 한국철도학회 2007년도 추계학술대회 논문집
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    • pp.1158-1164
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    • 2007
  • Recently, the demand on the practical application of life-cycle cost effectiveness for design and rehabilitation of civil infrastructure is rapidly growing unprecedentedly in civil engineering practice. Accordingly, it is expected that the life-cycle cost in the 21st century will become a new paradigm for all engineering decision problems in practice. However, in spite of impressive progress in the researches on the LCC, so far, most researches in Koreahave only focused on roadway bridges, which are not applicable to railway bridges. Thus, this paper presents the formulation models and methods for uncertainty-based LCCA for railroad bridges consideringboth objective statistical data available in the agency database of railroad bridges management and subjective data obtained form interviews with experts of the railway agency, which are used to anew uncertainty-based expected maintenance/repair costs including lifetime indirect costs. For reliable assessment of the life-cycle maintenance/repair costs, statistical analysis considering maintenance history data and survey data including the subjective judgments of railway experts on maintenance/management of railroad bridges, are performed to categorize critical maintenance items and associated expected costs and uncertainty-based deterioration models are developed. Finally, the formulation for simulation-based LCC analysis of railway bridges with uncertainty-based deterioration models are applied to the design-decision problem, which is to select an optimal bridge type having minimum Life-Cycle cost among various railway bridges types such as steel plate girder bridge, and prestressed concrete girder bridge in the basic design phase.

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EP Based PSO Method for Solving Multi Area Unit Commitment Problem with Import and Export Constraints

  • Venkatesan, K.;Selvakumar, G.;Rajan, C. Christober Asir
    • Journal of Electrical Engineering and Technology
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    • 제9권2호
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    • pp.415-422
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    • 2014
  • This paper presents a new approach to solve the multi area unit commitment problem (MAUCP) using an evolutionary programming based particle swarm optimization (EPPSO) method. The objective of this paper is to determine the optimal or near optimal commitment schedule for generating units located in multiple areas that are interconnected via tie lines. The evolutionary programming based particle swarm optimization method is used to solve multi area unit commitment problem, allocated generation for each area and find the operating cost of generation for each hour. Joint operation of generation resources can result in significant operational cost savings. Power transfer between the areas through the tie lines depends upon the operating cost of generation at each hour and tie line transfer limits. Case study of four areas with different load pattern each containing 7 units (NTPS) and 26 units connected via tie lines have been taken for analysis. Numerical results showed comparing the operating cost using evolutionary programming-based particle swarm optimization method with conventional dynamic programming (DP), evolutionary programming (EP), and particle swarm optimization (PSO) method. Experimental results show that the application of this evolutionary programming based particle swarm optimization method has the potential to solve multi area unit commitment problem with lesser computation time.

이기종 저장장치를 위한 제거 비용 평가 기반 캐시 관리 기법 (A Cache Management Technique Based on Eviction Cost Estimation for Heterogeneous Storage Devices)

  • 박세진;박찬익
    • 대한임베디드공학회논문지
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    • 제7권3호
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    • pp.129-134
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    • 2012
  • The objective of cache is to reduce I/O access of physical storage device so that user accesses their data faster. Traditionally, the most important metric to measure the performance of cache is hitratio. Thus, when the cache maintains hitratio high, it is regarded as a good cache replacement policy. However, the cache miss latency is different when the storages are heterogeneous. Though the cache hitratio is high, if the cache often misses with low performance disk, then the user experiences low performance. To address this problem we proposed eviction cost estimation based cache management. In our result, the eviction cost estimation based cache management has 10~30% throughput improvement compared with LRU cache management.

신뢰성 지수의 민감도 해석을 이용한 신뢰성에 기초한 최적설계 (Reliability-Based Optimization using Sensitivity Analysis of Reliability Index)

  • 조효남;민대홍;권우성
    • 한국전산구조공학회:학술대회논문집
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    • 한국전산구조공학회 2000년도 가을 학술발표회논문집
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    • pp.101-108
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    • 2000
  • An optimum design algorithm using efficient reanalysis is proposed for reliability-based optimization problems formulated as the minimization of initial cost and expected failure cost with reliability constraints. The reliability-based optimization is high cost to evaluate objective function and constraints needed reliability analysis. Therefore the sensitivity analysis of reliability index for approximated reanalysis is necessary. In this paper, three solution approaches are suggested and tested. The approaches include : (1) sensitivity analysis using finite difference; (2) sensitivity analysis using automatic differentiation (AD); and (3) sensitivity analysis with respect to intermediate variables using AD. Numerical example is optimized to show the reliability and effectiveness of the new algorithm.

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A STUDY ON RISK WEIGHT USING FUZZY IN REAL ESTATE DEVELOPMENT PROJECTS

  • Sung Cho;Kyung-ha Lee ;Yong Cho ;Joon-Hong Paek
    • 국제학술발표논문집
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    • The 3th International Conference on Construction Engineering and Project Management
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    • pp.1176-1182
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    • 2009
  • Due to recession in real estate market, interest of risk analysis is increasing. Feasibility study in the first stage takes a great role in a project. There are not objectified tools which are able to cope with uncertainty of project, and feasibility study based on selected method of determinism does not include liquidity of weight risk. Also, shortage of consideration for subjective and atypical external factors causes inappropriate results. Therefore, this study proposes feasibility study model focused on risk factor influences in construction cost and sales cost. Considering effective level of cost based on objective risk factors and probable weight of risk by this model, real workers are able to bring correct and scientific decisions better than former method based on selective analysis of real estate development.

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