• 제목/요약/키워드: objective cost function

검색결과 464건 처리시간 0.02초

처짐과 무게를 고려한 주물 프레임의 다중목적 근사최적설계 (Approximate Multi-Objective Optimization of Robot Casting Considering Deflection and Weight)

  • 최하영;이종수;박준오
    • 한국생산제조학회지
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    • 제21권6호
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    • pp.954-960
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    • 2012
  • Nowadays, rapidly changing and unstable global economic environments request a lot of roles to engineers. In this situation, product should be designed to make more profit by cost down and to satisfy distinguished performance comparing to other competitive ones. In this research, the optimization design of the industrial robot casting will be done. The weight and deflection have to be reduced as objective functions and stress has to be constrained under some constant value. To reduce time cost, CCD (Central Composite Design) will be used to make experimental design. And RSM (Response Surface Methodology) will be taken to make regression model for objective functions and constraint function. Finally, optimization will be done with Genetic Algorithm. In this problem, the objective functions are multiple, so NSGA-II which is brilliant and efficient for such a problem will be used. For the solution quality check, the diversity between Pareto solutions will be also checked.

신재생에너지 발전원을 고려한 발전기 예방정비계획수립에 관한 연구 (A Study on Generator Maintenance Scheduling Considering Renewable Energy Generators)

  • 이연찬;오웅진;최재석;정명훈
    • 전기학회논문지
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    • 제67권5호
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    • pp.601-610
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    • 2018
  • The purpose of this paper is to establish a new optimum Generator Maintenance Scheduling(GMS) considering renewable energy generator. In this paper, the total renewable energy generation is estimated using hourly capacity factor of renewable energy generator. The GMS was optimized with the objective function of maximizing the minimum reserve rate, minimizing the probabilistic production cost, minimizing the loss of load expectation, and minimizing $CO_2$ emissions. In the case study of this paper, GMS considering renewable energy and GMS not considering renewable energy are shown by each objective function. And it shows scenarios of the reliability, the environmental and economical factors when two nuclear power plants inputted and ten coal thermal power plants shut downed respectively.

Structural damage identification of truss structures using self-controlled multi-stage particle swarm optimization

  • Das, Subhajit;Dhang, Nirjhar
    • Smart Structures and Systems
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    • 제25권3호
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    • pp.345-368
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    • 2020
  • The present work proposes a self-controlled multi-stage optimization method for damage identification of structures utilizing standard particle swarm optimization (PSO) algorithm. Damage identification problem is formulated as an inverse optimization problem where damage severity in each element of the structure is considered as optimization variables. An efficient objective function is formed using the first few frequencies and mode shapes of the structure. This objective function is minimized by a self-controlled multi-stage strategy to identify and quantify the damage extent of the structural members. In the first stage, standard PSO is utilized to get an initial solution to the problem. Subsequently, the algorithm identifies the most damage-prone elements of the structure using an adaptable threshold value of damage severity. These identified elements are included in the search space of the standard PSO at the next stage. Thus, the algorithm reduces the dimension of the search space and subsequently increases the accuracy of damage prediction with a considerable reduction in computational cost. The efficiency of the proposed method is investigated and compared with available results through three numerical examples considering both with and without noise. The obtained results demonstrate the accuracy of the present method can accurately estimate the location and severity of multi-damage cases in the structural systems with less computational cost.

Structural damage identification using an iterative two-stage method combining a modal energy based index with the BAS algorithm

  • Wang, Shuqing;Jiang, Yufeng;Xu, Mingqiang;Li, Yingchao;Li, Zhixiong
    • Steel and Composite Structures
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    • 제36권1호
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    • pp.31-45
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    • 2020
  • The purpose of this study is to develop an effective iterative two-stage method (ITSM) for structural damage identification of offshore platform structures. In each iteration, a new damage index, Modal Energy-Based Damage Index (MEBI), is proposed to help effectively locate the potential damage elements in the first stage. Then, in the second stage, the beetle antenna search (BAS) algorithm is used to estimate the damage severity of these elements. Compared with the well-known particle swarm optimization (PSO) algorithm and genetic algorithm (GA), this algorithm has lower computational cost. A modal energy based objective function for the optimization process is proposed. Using numerical and experimental data, the efficiency and accuracy of the ITSM are studied. The effects of measurement noise and spatial incompleteness of mode shape are both considered. All the obtained results show that under these influences, the ITSM can accurately identify the true location and severity of damage. The results also show that the objective function based on modal energy is most suitable for the ITSM compared with that based on flexibility and weighted natural frequency-mode shape.

불확실성을 고려한 교량 하부구조 최적설계 (Optimal Design of Bridge Substructure Considering Uncertainty)

  • 박장호;신영석;신욱범;이재우
    • 한국전산구조공학회:학술대회논문집
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    • 한국전산구조공학회 2008년도 정기 학술대회
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    • pp.387-390
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    • 2008
  • The importance of the life cycle cost analysis for construction projects of bridge has been recognized over the last decades. Accordingly, theoretical models, guidelines, and supporting softwares have been developed for the life cycle cost analysis of bridges. However, it is difficult to predict life cycle cost considering uncertainties precisely. This paper presents methodology for optimal design of substructure for a steel box bridge. Total life cycle cost for the service life is calculated as sum of initial cost, damage cost considering uncertainty, maintenance cost, repair and rehabilitation cost. The optimization method is applied to design of a bridge substructure with minimal cost, in which the objective function is set to life cycle cost and constraints are formulated on the basis of Korean Bridge Design Specification. Initial cost is calculated based on standard costs of the Korea Construction Price Index and damage cost on the damage probabilities to consider the uncertainty of load and resistance. An advanced first-order second moment method is used as a practical tool for reliability analysis using damage probability. Maintenance cost and cycle is determined by a stochastic method and user cost includes traffic operation costs and time delay costs.

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교량의 생애주기비용 분석을 위한 비용함수 모델 및 시스템 개발 (Development of System and Cost Function Model for Life Cycle Cost Analysis of Bridge)

  • 박미연;선종완;엄인수;조효남
    • 한국전산구조공학회:학술대회논문집
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    • 한국전산구조공학회 2005년도 춘계 학술발표회 논문집
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    • pp.704-711
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    • 2005
  • Recently Life Cycle Cost Analysis for civil infrastructures such as pavements, bridges, and dams has been emphasized However, so far, there are few systems available for life cycle cost analysis of bridges at design stage. Therefore, the objective of this paper is to develop a user-friendly life-cycle cost analysis system for LCC-effective optimal design decision making at design stage. The program is based on the proposed LCC model, formulation, analysis modules and systematic procedure that suit Korean construction conditions. It is expected that the developed system can be effectively utilized for more LCC-effective design of bridges. It is applied to an actual bridge design project in order to demonstrate its effectiveness and applicability.

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공공차량 경로문제 해법연구 (Public Vehicle Routing Problem Algorithm)

  • 장병만;박순달
    • 한국경영과학회지
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    • 제14권2호
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    • pp.53-66
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    • 1989
  • The Public Vehicle Routing Problem (PVRP) is to find the minimum total cost routes of M or less Public-Vehicles to traverse the required arcs(streets) at least once, and return to their starting depot on a directed network. In this paper, first, a mathematical model is formulated as minimal cost flow model with illegal subtour elimination constraints, and with the fixed cost and routing cost as an objective function. Second, an efficient branch and bound algorithm is developed to obtain an exact solution. A subproblem in this method is a minimal cost flow problem relaxing illegal subtour elimination constraints. The branching strategy is a variable dichotomy method according to the entering nonrequired arcs which are candidates to eneter into an illegal subtour. To accelerate the fathoming process, a tighter lower bound of a candidate subproblem is calculated by using a minimum reduced coast of the entering nonrequired arcs. Computational results based on randomly generated networks report that the developed algorithm is efficient.

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수요와 조도계수의 불확실성을 고려한 상수도관망의 최적설계 (Optimal Design of Water Distribution System considering the Uncertainties on the Demands and Roughness Coefficients)

  • 정동휘;정건희;김중훈
    • 한국방재학회 논문집
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    • 제10권1호
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    • pp.73-80
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    • 2010
  • 상수도관망의 최적설계는 단목적함수와 고정된 수리학적 변수로 구성된 비용최소화의 문제로 시작되었다. 하지만, 미래의 불확실한 수요량의 변동과 같이 상수도관망 내에 존재하는 여러 불확실성을 고려하여 설계하는 것이 실제 상수도관망의 거동을 보다 적절히 예측하는 것이다. 따라서 상수도관망 내 존재하는 불확실성을 양적으로 고려하는 다양한 방법이 연구되어 상수도관망의 최적설계에 반영되었고, 다목적함수를 사용한 최적화문제도 다루게 되었다. 본 연구에서는 관망의 절점에서의 수요량과 관의 조도계수를 불확실성을 가진 변수로 두고, 비용 최소화와 관망의 강건성 (Robustness)을 최대화 하는 두 가지 목적함수를 가진 다목적함수 최적화 문제를 다루었다. 최적화 과정은 비용최소화와 불확실성을 고려한 최종 최적화의 두 과정으로 나뉜다. 각 절점에서의 수요량과 관의 조도계수는 베타확률밀도함수 (Beta PDF)를 사용, Latin Hypercube 샘플링 방법으로 불확실성을 고려하였고, 다목적함수의 최적화는 유전자 알고리듬 (Multi-objective Genetic Algorithms, MOGA)을 사용하였다. 제안된 방법은 New York Tunnels이라는 실제 상수도관망에 적용하여 적용성을 검증 하였고 그 결과를 분석하였다. 다목적 최적화 문제에서 최적화가 진행될 수 록 초기 값에 모여 있던 점들이 그 점 주위를 시작으로 해 공간에 최적 해를 찾아 오른쪽 아래 부분으로 탐색해 나가는 것을 확인할 수 있었고 최적설계의 해는 해 공간에서 Pareto Front를 구성하며 파레토 최적해를 구하였다.

유전자 알고리즘을 이용한 최적의 가공 조건 결정 (Determination of Optimal Machining Parameters Using Genetic Algorithm)

  • 최경현;육성훈
    • 동력기계공학회지
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    • 제3권4호
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    • pp.63-68
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    • 1999
  • The determination of the optimal machining parameters in metal cutting, such as cutting speed, feed rate, and depth of cut, is an important aspect in an economic manufacturing process. The main objective in general is either to minimize the production cost or to maximize the production rate. Also there are constraints on all the machining operations which put restrictions on the choice of the machining parameters. In this paper as an objective function the production cost is considered with two constraints, surface finish and cutting power. Genetic Algorithm is applied to determine the optimum machining parameters, and the effectiveness of the applied algorithm is demonstrated by means of an example, turning operation.

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Minimum cost design of RCMRFs based on consistent approximation method

  • Habibi, Alireza;Shahryari, Mobin;Rostami, Hasan
    • Computers and Concrete
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    • 제26권1호
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    • pp.1-10
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    • 2020
  • In this paper, a procedure for automated optimized design of reinforced concrete frames has been presented. The procedure consists of formulation and solution of the design problem in the form of an optimization problem. The minimization of total cost of R/C frame has been taken as the objective of optimization problem. In this research, consistent approximation method is applied to explicitly formulate constraints and objective function in terms of the design variables. In the presented method, the primary optimization problem is replaced with a sequence of explicit sub-problems. Each sub-problem is efficiently solved using the Sequential Quadratic Programming (SQP) method. The proposed method is demonstrated through a four-story frame and an eight-story frame, and the optimum results are compared with those in the available literature. It is shown that the proposed method can be easily applied to obtain rational, reliable, economical and practical designs for Reinforced Concrete Moment Resisting Frames (RCMRFs) while it is converged after a few analyses.