• Title/Summary/Keyword: optimization procedure

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Analysis of the Case on Kitchen Equipment of Hotel Adopted Pattern Systemic Layout Planning(SLP) - Focusing on Cooking Process - (체계적 배치(SLP)기법을 적용한 호텔주방 설비배치의 사례분석 - 조리공정을 중심으로 -)

  • 조성호
    • Culinary science and hospitality research
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    • v.9 no.2
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    • pp.98-114
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    • 2003
  • This paper is written to analyze systematically the varieties of informations about cooking stream procedure on the basis of the basic theory of installation and arrangement such as SLP(Systemic Layout Planning) and to deduce the plan for the device, installation and arrangement suitable to cooking stream procedure. Through the substantial improvement in the modeling of hotel L, the optimization of the capacity of installation and arrangement, and the reduction of food resource stream and its movement and through the analysis of cooking stream procedure by disposing and dividing the main kitchen into three individual ones, the improvement of productivity in comprehensive cookery such as the specialization and equalization of cooking procedure and improvement effect of the price-reduction. Moreover, as for the problem of arrangement of installation, it was displayed that the effect went up to twice through the flexible production-related systems such as the improvement of arrangement, reduction of cooking preparation time, the standardization of cookery.

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A Study on Dynamic Parameter Design Procedure Considering the Signal Factor and the Quality Characteristics with Continuous Variable (신호인자와 특성치가 연속형 변수인 경우를 고려한 동적파라미터 설계 절차에 관한 연구)

  • 배홍석;이만웅;송서일
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.19 no.39
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    • pp.243-254
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    • 1996
  • In this study, a model and an analysis method for parameter design is presented a linear relation between the input signal and the ideal value of a performance characteristic. Furthermore, There presented a new performance measure, expected quality loss after adjustment, which is proved to be equivalent to Taguchi's SN ratio approximately. On the basis of this, a two-step optimization procedure is proposed for parameter design considering the signal factor and the quality characteristics with continuous variable. Proposed procedure and Taguchi two-stage procedure are compared.

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Design Optimization of Wake Equalizing Duct Using CFD (CFD를 이용한 Wake Equalizing Duct의 최적설계)

  • Lee, Ho-Sung;Kim, Dong-Joon
    • Journal of Ocean Engineering and Technology
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    • v.25 no.4
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    • pp.42-47
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    • 2011
  • In this paper, wake equalizing duct (WED) form optimization was carried out using computational fluid dynamics (CFD) techniques. A WED is a ring-shaped flow vane with a foil-type cross-section fitted to a hull in front of the upper propeller area. The main advantage of a WED is the power savings resulting from the uniformity of the velocity distribution on the propeller plane, a reduction in the flow separation at the aft-body, and lift generation with a forward force component on the foil section. This paper intends to evaluate these functions and find an optimized WED form for minimizing the viscous resistance and equalizing the wake distribution. In the optimization process, the study uses four WED parameters: the angle of the section, longitudinal location, and angles of the axes for the half rings against the longitudinal and transverse planes of the ship. KRISO 300K VLCC2 (KVLCC2) is chosen as an example ship to demonstrate the WED optimization. The optimization procedure uses genetic algorithms (GAs), a gradient-based optimizer for the refinement of the solution, and Non-dominated Sorting GA-II(NSGA-II) for Multiobjective Optimization. The results show that the optimized WED can reduce the viscous resistance at the expense of the uniformity of the wake distribution.

Study on the Weight Optimization of Excavator Attachments Considering Durability (굴삭기 작업장치 내구 경량 최적화 기법 연구)

  • Kim, Pan-Young;Kim, Hyun-Gi;Park, Jin-Soo;Hwang, Jae-Bong;Song, Kyu-Sam
    • Proceedings of the KSME Conference
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    • 2007.05a
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    • pp.349-353
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    • 2007
  • The main functions of excavator are mainly carried out by excavator attachments such as arm and boom. These components should be designed to be light as well as durable enough because their effects on the whole structure are significant. In this paper, an optimization procedure for lightweight design considering fatigue strength for excavator attachments is presented. The weight of attachments and allowable fatigue stresses at critical areas are used as objective function and constraints, respectively, in which design variables are the thickness of the plates of attachments. The simulated annealing search method is adopted for a global optimization solution. Besides, the response surface method using the artificial neural network is used to simulate constraint function for the sake of practical fast calculation. Some example case of optimization is presented here for a sample excavator. This weight optimization is expected to contribute to a considerable improvement of fuel efficiency of excavator.

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Reliability-based design optimization of structural systems using a hybrid genetic algorithm

  • Abbasnia, Reza;Shayanfar, Mohsenali;Khodam, Ali
    • Structural Engineering and Mechanics
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    • v.52 no.6
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    • pp.1099-1120
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    • 2014
  • In this paper, reliability-based design optimization (RBDO) of structures is addressed. For this purpose, the global search and optimization capabilities of genetic algorithm (GA) are combined with the efficiency and reasonable accuracy of an advanced moment-based finite element reliability method. For performing RBDO, three variants of GA including a real-coded, a binary-coded and an improved binary-coded GA are developed. In these methods, GA performs (finite element) reliability analyses to evaluate reliability constraints. For truss structures which include finite element modeling, reliability constraints are evaluated using finite element reliability analysis. Response sensitivity required for finite element reliability analysis is obtained by direct differentiation method (DDM) rather than finite difference method (FDM). The proposed methods are examined within four standard test examples and real-world design problems. The results illustrate the superiority and efficiency of the improved binary-coded GA. Results also illustrate that DDM significantly reduces the computational cost and improves the efficiency of the optimization procedure.

Optimization of injection molding process for car fender in consideration of energy efficiency and product quality

  • Park, Hong Seok;Nguyen, Trung Thanh
    • Journal of Computational Design and Engineering
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    • v.1 no.4
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    • pp.256-265
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    • 2014
  • Energy efficiency is an essential consideration in sustainable manufacturing. This study presents the car fender-based injection molding process optimization that aims to resolve the trade-off between energy consumption and product quality at the same time in which process parameters are optimized variables. The process is specially optimized by applying response surface methodology and using non-dominated sorting genetic algorithm II (NSGA II) in order to resolve multi-object optimization problems. To reduce computational cost and time in the problem-solving procedure, the combination of CAE-integration tools is employed. Based on the Pareto diagram, an appropriate solution is derived out to obtain optimal parameters. The optimization results show that the proposed approach can help effectively engineers in identifying optimal process parameters and achieving competitive advantages of energy consumption and product quality. In addition, the engineering analysis that can be employed to conduct holistic optimization of the injection molding process in order to increase energy efficiency and product quality was also mentioned in this paper.

Optimization of 3G Mobile Network Design Using a Hybrid Search Strategy

  • Wu Yufei;Pierre Samuel
    • Journal of Communications and Networks
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    • v.7 no.4
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    • pp.471-477
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    • 2005
  • This paper proposes an efficient constraint-based optimization model for the design of 3G mobile networks, such as universal mobile telecommunications system (UMTS). The model concerns about finding a set of sites for locating radio network controllers (RNCs) from a set of pre-defined candidate sites, and at the same time optimally assigning node Bs to the selected RNCs. All these choices must satisfy a set of constraints and optimize an objective function. This problem is NP-hard and consequently cannot be practically solved by exact methods for real size networks. Thus, this paper proposes a hybrid search strategy for tackling this complex and combinatorial optimization problem. The proposed hybrid search strategy is composed of three phases: A constraint satisfaction method with an embedded problem-specific goal which guides the search for a good initial solution, an optimization phase using local search algorithms, such as tabu algorithm, and a post­optimization phase to improve solutions from the second phase by using a constraint optimization procedure. Computational results show that the proposed search strategy and the model are highly efficient. Optimal solutions are always obtained for small or medium sized problems. For large sized problems, the final results are on average within $5.77\%$ to $7.48\%$ of the lower bounds.

Numerical Optimization for Performance Improvement of a Tunnel Ventilation Jet fan (터널 환기용 제트홴의 성능 향상을 위한 수치최적화)

  • Kim, Joon-Hyung;Kim, Jin-Hyuk;Kim, Kwang-Yong;Yoon, Joon-Yong;Choi, Young-Seok;Yang, Sang-Ho
    • The KSFM Journal of Fluid Machinery
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    • v.14 no.5
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    • pp.63-68
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    • 2011
  • This paper presents an optimization procedure for performance improvement of a tunnel ventilation jet fan. Optimization techniques based on response surface approximation (RSA) are employed to improve the aerodynamic performance of a tunnel ventilation jet fan. For numerical analysis, three-dimensional Renolds- averaged Navier-Stokes (RANS) equations with shear stress transport turbulence model are discretized by using finite volume approximations and solved on hexahedral grids to evaluate the total efficiency at the operating condition as the objective function. Four geometric variables defining the meridional length and the thickness profile at the hub and shroud in the jet fan rotor are selected as design variables for the numerical optimization. The results of the numerical optimization show that the total efficiency of the optimized model is significantly improved in comparison with the base model.

An integrated particle swarm optimizer for optimization of truss structures with discrete variables

  • Mortazavi, Ali;Togan, Vedat;Nuhoglu, Ayhan
    • Structural Engineering and Mechanics
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    • v.61 no.3
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    • pp.359-370
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    • 2017
  • This study presents a particle swarm optimization algorithm integrated with weighted particle concept and improved fly-back technique. The rationale behind this integration is to utilize the affirmative properties of these new terms to improve the search capability of the standard particle swarm optimizer. Improved fly-back technique introduced in this study can be a proper alternative for widely used penalty functions to handle existing constraints. This technique emphasizes the role of the weighted particle on escaping from trapping into local optimum(s) by utilizing a recursive procedure. On the other hand, it guaranties the feasibility of the final solution by rejecting infeasible solutions throughout the optimization process. Additionally, in contrast with penalty method, the improved fly-back technique does not contain any adjustable terms, thus it does not inflict any extra ad hoc parameters to the main optimizer algorithm. The improved fly-back approach, as independent unit, can easily be integrated with other optimizers to handle the constraints. Consequently, to evaluate the performance of the proposed method on solving the truss weight minimization problems with discrete variables, several benchmark examples taken from the technical literature are examined using the presented method. The results obtained are comparatively reported through proper graphs and tables. Based on the results acquired in this study, it can be stated that the proposed method (integrated particle swarm optimizer, iPSO) is competitive with other metaheuristic algorithms in solving this class of truss optimization problems.

Bayesian Optimization Analysis of Containment-Venting Operation in a Boiling Water Reactor Severe Accident

  • Zheng, Xiaoyu;Ishikawa, Jun;Sugiyama, Tomoyuki;Maruyama, Yu
    • Nuclear Engineering and Technology
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    • v.49 no.2
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    • pp.434-441
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    • 2017
  • Containment venting is one of several essential measures to protect the integrity of the final barrier of a nuclear reactor during severe accidents, by which the uncontrollable release of fission products can be avoided. The authors seek to develop an optimization approach to venting operations, from a simulation-based perspective, using an integrated severe accident code, THALES2/KICHE. The effectiveness of the containment-venting strategies needs to be verified via numerical simulations based on various settings of the venting conditions. The number of iterations, however, needs to be controlled to avoid cumbersome computational burden of integrated codes. Bayesian optimization is an efficient global optimization approach. By using a Gaussian process regression, a surrogate model of the "black-box" code is constructed. It can be updated simultaneously whenever new simulation results are acquired. With predictions via the surrogate model, upcoming locations of the most probable optimum can be revealed. The sampling procedure is adaptive. Compared with the case of pure random searches, the number of code queries is largely reduced for the optimum finding. One typical severe accident scenario of a boiling water reactor is chosen as an example. The research demonstrates the applicability of the Bayesian optimization approach to the design and establishment of containment-venting strategies during severe accidents.