• Title/Summary/Keyword: Crossover Process

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An Optimal Auto-Tuning of PID Controller using Evolution Programs (II) (진화 프로그램을 사용한 PID제어기의 최적 자동동조 (I I))

  • 이수흠;이내일;방근태
    • Proceedings of the Korea Institute of Convergence Signal Processing
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    • 2000.08a
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    • pp.109-112
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    • 2000
  • We propose a new method to deal with the optimized auto-tuning for the PID controller which is used to the process-control In various fields. First of all, in this method, 1st order delay system with dead time which is modelled from the unit step response of the system is Pade -approximated, then initial values are determined by the Ziegler-Nichols method. After inputting constraints of evolution programs, we perform crossover and mutation to generate the descendant generation. The advantage of this method is better than the Ziegler-Nickels method in characteristic of output and has extent of applying without limit of K, L, T.

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Effects of Two Music Therapy Methods on Agitation and Anxiety among Patients Weaning off Mechanical Ventilation: A Pilot Study

  • Park, Jong Yoen;Park, Soohyun
    • Journal of Korean Academy of Fundamentals of Nursing
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    • v.26 no.2
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    • pp.136-143
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    • 2019
  • Purpose: The feasibility and differential effects of two music therapy methods (interventions with preferred music vs. classical relaxation music) were done to examine the effects on agitation and anxiety in patients weaning off mechanical ventilation. Methods: This pilot study was conducted using a crossover design. Six patients listened to preferred music choices and classical relaxation music. Anxiety scores were measured using the Richmond Agitation Sedation Scale (RASS), State-Trait Anxiety Inventory (STAI), and visual analog scale (VAS). Results: Patients showed a significant decrease in agitation and anxiety after both the preferred and classical relaxation music interventions. The difference in the effects of preferred music and that of classical relaxation music was not significant. As for feasibility, patients exhibited a change in agitated behaviors after the music interventions by not trying to take off medical devices and quietly listening to the music, and by smiling and moving lips along with the lyrics while listening. Conclusion: Music interventions which centered on either patients' preferences or classical relaxation music to enhance relaxation, helped reduce agitation and anxiety during the mechanical ventilation weaning process.

Pore-filling anion conducting membranes and their cell performance for a solid alkaline fuel cell (세공충진 음이온 전도성막의 제조 및 이를 이용한 고체알칼리 연료전지 성능 평가)

  • Choi, Youngwoo;Lee, Misoon;Park, Gugon;Yim, Sungdae;Yang, Taehyun;Kim, Changsoo
    • 한국신재생에너지학회:학술대회논문집
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    • 2010.06a
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    • pp.129.2-129.2
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    • 2010
  • AEM which were used for solid alkaline fuel cell(SAFC) were prepared by photo polymerization in method pore-filling with various quaternary ammonium cationic monomers and crosslinkers without an amination process. Their specific thermal and chemical properties were characterized through various analyses and the physico-chemical properties of the prepared electrolyte membranes such as swelling behavior, ion exchange capacity and ionic conductivity were also investigated in correlation with the electrolyte composition. The polymer electrolyte membranes prepared in this study have a very wide hydroxyl ion conductivity range of 0.01 - 0.45S/cm depending on the composition ratio of the electrolyte monomer and crosslinking agent used for polymerization. However, the hydroxyl ion conductivity of the membranes was relatively higher at the whole cases than those of commercial products such as A201 membrane of Tokuyama. These pore-filling membranes have also excellent properties such as smaller dimensional affects when swollen in solvents, higher mechanical strength, lowest electrolyte crossover through the membranes, and easier preparation process compared of traditional cast membranes. The prepared membranes were then applied to solid alkaline fuel cell and it was found comparable fuel cell performance to A201 membrane of Tokuyama.

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Design of Optimal Fuzzy Logic based PI Controller using Multiple Tabu Search Algorithm for Load Frequency Control

  • Pothiya Saravuth;Ngamroo Issarachai;Runggeratigul Suwan;Tantaswadi Prinya
    • International Journal of Control, Automation, and Systems
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    • v.4 no.2
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    • pp.155-164
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    • 2006
  • This paper focuses on a new optimization technique of a fuzzy logic based proportional integral (FLPI) load frequency controller by the multiple tabu search (MTS) algorithm. Conventionally, the membership functions and control rules of fuzzy logic control are obtained by trial and error method or experiences of designers. To overcome this problem, the MTS algorithm is proposed to simultaneously tune proportional integral gains, the membership functions and control rules of a FLPI load frequency controller in order to minimize the frequency deviations of the interconnected power system against load disturbances. The MTS algorithm introduces additional techniques for improvement of the search process such as initialization, adaptive search, multiple searches, crossover and restart process. Simulation results explicitly show that the performance of the proposed FLPI controller is superior to conventional PI and FLPI controllers in terms of overshoot and settling time. Furthermore, the robustness of the proposed FLPI controller under variation of system parameters and load change are higher than that of conventional PI and FLPI controllers.

A study on the optimal sizing and topology design for Truss/Beam structures using a genetic algorithm (유전자 알고리듬을 이용한 트러스/보 구조물의 기하학적 치수 및 토폴로지 최적설계에 관한 연구)

  • 박종권;성활경
    • Journal of the Korean Society for Precision Engineering
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    • v.14 no.3
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    • pp.89-97
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    • 1997
  • A genetic algorithm (GA) is a stochastic direct search strategy that mimics the process of genetic evolution. The GA applied herein works on a population of structural designs at any one time, and uses a structured information exchange based on the principles of natural selection and wurvival of the fittest to recombine the most desirable features of the designs over a sequence of generations until the process converges to a "maximum fitness" design. Principles of genetics are adapted into a search procedure for structural optimization. The methods consist of three genetics operations mainly named selection, cross- over and mutation. In this study, a method of finding the optimum topology of truss/beam structure is pro- posed by using the GA. In order to use GA in the optimum topology problem, chromosomes to FEM elements are assigned, and a penalty function is used to include constraints into fitness function. The results show that the GA has the potential to be an effective tool for the optimal design of structures accounting for sizing, geometrical and topological variables.variables.

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Parametric identification of the Bouc-Wen model by a modified genetic algorithm: Application to evaluation of metallic dampers

  • Shu, Ganping;Li, Zongjing
    • Earthquakes and Structures
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    • v.13 no.4
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    • pp.397-407
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    • 2017
  • With the growing demand for metallic dampers in engineering practice, it is urgent to establish a reasonable approach to evaluating the mechanical performance of metallic dampers under seismic excitations. This paper introduces an effective method for parameter identification of the modified Bouc-Wen model and its application to evaluating the fatigue performance of metallic dampers (MDs). The modified Bouc-Wen model which eliminates the redundant parameter is used to describe the hysteresis behavior of MDs. Relations between the parameters of the modified Bouc-Wen model and the mechanical performance parameters of MDs are studied first. A modified Genetic Algorithm using real-integer hybrid coding with relative fitness as well as adaptive crossover and mutation rates (called RFAGA) is then proposed to identify the parameters of the modified Bouc-Wen model. A reliable approach to evaluating the fatigue performance of the MDs with respect to the Chinese Code for Seismic Design of Buildings (GB 50011-2010) is finally proposed based on the research results. Experimental data are employed to demonstrate the process and verify the effectiveness of the proposed approach. It is shown that the RFAGA is able to converge quickly in the identification process, and the simulation curves based on the identification results fit well with the experimental hysteresis curves. Furthermore, the proposed approach is shown to be a useful tool for evaluating the fatigue performance of MDs with respect to the Chinese Code for Seismic Design of Buildings (GB 50011-2010).

Lifting Lug by the Change of form Using Multivariate Functions: An Optimal Design Study (다변수 함수를 이용한 형상 변화에 따른 리프팅 러그의 최적 설계에 관한 연구)

  • Choi, Kyung-Shin;Kim, Ji-Jun;Lee, Ji-Han;Chan, Gwang-Woo
    • Journal of the Korean Society of Manufacturing Process Engineers
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    • v.20 no.4
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    • pp.31-38
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    • 2021
  • In this paper, we proposed an optimal design for determining the shape of a lifting lug freely by applying a multivariate function to the D-type lug, which is commonly used in shipyards. We derived the optimal aspect ratio of the lug through structural analysis and analyzed the safety and behavior of the lug aspect ratio. As a result, two types of final candidates, both lighter than the existing lug weight, were suitable for the ratio. They were found to have the greatest force at an angle of 45 degrees when a load of 100 tons was imposed. When the horizontal and vertical feature ratio of the lug was 1:3, it showed excellent results in terms of safety rates while maintaining weight reduction and functional aspects.

Concept Optimization for Mechanical Product Using Genetic Algorithm

  • Huang Hong Zhong;Bo Rui Feng;Fan Xiang Feng
    • Journal of Mechanical Science and Technology
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    • v.19 no.5
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    • pp.1072-1079
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    • 2005
  • Conceptual design is the first step in the overall process of product design. Its intrinsic uncertainty, imprecision, and lack of information lead to the fact that current conceptual design activities in engineering have not been computerized and very few CAD systems are available to support conceptual design. In most of the current intelligent design systems, approach of principle synthesis, such as morphology matrix, bond graphic, or design catalogues, is usually adopted to deal with the concept generation, in which optional concepts are generally combined and enumerated through function analysis. However, as a large number of concepts are generated, it is difficult to evaluate and optimize these design candidates using regular algorithm. It is necessary to develop a new approach or a tool to solve the concept generation. Generally speaking, concept generation is a problem of concept synthesis. In substance, this process of developing design candidate is a combinatorial optimization process, viz., the process of concept generation can be regarded as a solution for a state-place composed of multi-concepts. In this paper, genetic algorithm is utilized as a feasible tool to solve the problem of combinatorial optimization in concept generation, in which the encoding method of morphology matrix based on function analysis is applied, and a sequence of optimal concepts are generated through the search and iterative process which is controlled by genetic operators, including selection, crossover, mutation, and reproduction in GA. Several crucial problems on GA are discussed in this paper, such as the calculation of fitness value and the criteria for heredity termination, which have a heavy effect on selection of better concepts. The feasibility and intellectualization of the proposed approach are demonstrated with an engineering case. In this work concept generation is implemented using GA, which can facilitate not only generating several better concepts, but also selecting the best concept. Thus optimal concepts can be conveniently developed and design efficiency can be greatly improved.

An Improved Genetic Algorithm for Integrated Planning and Scheduling Algorithm Considering Tool Flexibility and Tool Constraints (공구유연성과 공구관련제약을 고려한 통합공정일정계획을 위한 유전알고리즘)

  • Kim, Young-Nam;Ha, Chunghun
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.40 no.2
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    • pp.111-120
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    • 2017
  • This paper proposes an improved standard genetic algorithm (GA) of making a near optimal schedule for integrated process planning and scheduling problem (IPPS) considering tool flexibility and tool related constraints. Process planning involves the selection of operations and the allocation of resources. Scheduling, meanwhile, determines the sequence order in which operations are executed on each machine. Due to the high degree of complexity, traditionally, a sequential approach has been preferred, which determines process planning firstly and then performs scheduling independently based on the results. The two sub-problems, however, are complicatedly interrelated to each other, so the IPPS tend to solve the two problems simultaneously. Although many studies for IPPS have been conducted in the past, tool flexibility and capacity constraints are rarely considered. Various meta-heuristics, especially GA, have been applied for IPPS, but the performance is yet satisfactory. To improve solution quality against computation time in GA, we adopted three methods. First, we used a random circular queue during generation of an initial population. It can provide sufficient diversity of individuals at the beginning of GA. Second, we adopted an inferior selection to choose the parents for the crossover and mutation operations. It helps to maintain exploitation capability throughout the evolution process. Third, we employed a modification of the hybrid scheduling algorithm to decode the chromosome of the individual into a schedule, which can generate an active and non-delay schedule. The experimental results show that our proposed algorithm is superior to the current best evolutionary algorithms at most benchmark problems.

Evaluating Reverse Logistics Networks with Centralized Centers : Hybrid Genetic Algorithm Approach (집중형센터를 가진 역물류네트워크 평가 : 혼합형 유전알고리즘 접근법)

  • Yun, YoungSu
    • Journal of Intelligence and Information Systems
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    • v.19 no.4
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    • pp.55-79
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    • 2013
  • In this paper, we propose a hybrid genetic algorithm (HGA) approach to effectively solve the reverse logistics network with centralized centers (RLNCC). For the proposed HGA approach, genetic algorithm (GA) is used as a main algorithm. For implementing GA, a new bit-string representation scheme using 0 and 1 values is suggested, which can easily make initial population of GA. As genetic operators, the elitist strategy in enlarged sampling space developed by Gen and Chang (1997), a new two-point crossover operator, and a new random mutation operator are used for selection, crossover and mutation, respectively. For hybrid concept of GA, an iterative hill climbing method (IHCM) developed by Michalewicz (1994) is inserted into HGA search loop. The IHCM is one of local search techniques and precisely explores the space converged by GA search. The RLNCC is composed of collection centers, remanufacturing centers, redistribution centers, and secondary markets in reverse logistics networks. Of the centers and secondary markets, only one collection center, remanufacturing center, redistribution center, and secondary market should be opened in reverse logistics networks. Some assumptions are considered for effectively implementing the RLNCC The RLNCC is represented by a mixed integer programming (MIP) model using indexes, parameters and decision variables. The objective function of the MIP model is to minimize the total cost which is consisted of transportation cost, fixed cost, and handling cost. The transportation cost is obtained by transporting the returned products between each centers and secondary markets. The fixed cost is calculated by opening or closing decision at each center and secondary markets. That is, if there are three collection centers (the opening costs of collection center 1 2, and 3 are 10.5, 12.1, 8.9, respectively), and the collection center 1 is opened and the remainders are all closed, then the fixed cost is 10.5. The handling cost means the cost of treating the products returned from customers at each center and secondary markets which are opened at each RLNCC stage. The RLNCC is solved by the proposed HGA approach. In numerical experiment, the proposed HGA and a conventional competing approach is compared with each other using various measures of performance. For the conventional competing approach, the GA approach by Yun (2013) is used. The GA approach has not any local search technique such as the IHCM proposed the HGA approach. As measures of performance, CPU time, optimal solution, and optimal setting are used. Two types of the RLNCC with different numbers of customers, collection centers, remanufacturing centers, redistribution centers and secondary markets are presented for comparing the performances of the HGA and GA approaches. The MIP models using the two types of the RLNCC are programmed by Visual Basic Version 6.0, and the computer implementing environment is the IBM compatible PC with 3.06Ghz CPU speed and 1GB RAM on Windows XP. The parameters used in the HGA and GA approaches are that the total number of generations is 10,000, population size 20, crossover rate 0.5, mutation rate 0.1, and the search range for the IHCM is 2.0. Total 20 iterations are made for eliminating the randomness of the searches of the HGA and GA approaches. With performance comparisons, network representations by opening/closing decision, and convergence processes using two types of the RLNCCs, the experimental result shows that the HGA has significantly better performance in terms of the optimal solution than the GA, though the GA is slightly quicker than the HGA in terms of the CPU time. Finally, it has been proved that the proposed HGA approach is more efficient than conventional GA approach in two types of the RLNCC since the former has a GA search process as well as a local search process for additional search scheme, while the latter has a GA search process alone. For a future study, much more large-sized RLNCCs will be tested for robustness of our approach.