• Computers and Concrete
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• v.6 no.3
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• pp.253-268
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• 2009

This study aims to develop a cost-based high-performance concrete (HPC) mix optimization system based on an integrated approach using artificial neural networks (ANNs) and genetic algorithms (GA). ANNs are used to predict the three main properties of HPC, namely workability, strength and durability, which are used to evaluate fitness and constraint violations in the GA process. Multilayer back-propagation neural networks are trained using the results obtained from experiments and previous research. The correlation between concrete components and its properties is established. GA is employed to arrive at an optimal mix proportion of HPC by minimizing its total cost. A system prototype, called High Performance Concrete Mix-Design System using Genetic Algorithm and Neural Networks (HPCGANN), was developed in MATLAB. The architecture of the proposed system consists of three main parts: 1) User interface; 2) ANNs prediction models software; and 3) GA engine software. The validation of the proposed system is carried out by comparing the results obtained from the system with the trial batches. The results indicate that the proposed system can be used to enable the design of HPC mix which corresponds to its required performance. Furthermore, the proposed system takes into account the influence of the fluctuating unit price of materials in order to achieve the lowest cost of concrete, which cannot be easily obtained by traditional methods or trial-and-error techniques.

• Journal of Electrical Engineering and Technology
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• v.4 no.3
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• pp.353-359
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• 2009

This paper proposes a novel technique for calculating the security costs that properly includes ramping constraints in the operation of a deregulated power system. The ramping process is modeled by a piecewise linear function with certain assumptions. During this process, a ramping cost is incurred if the permissible limits are exceeded. The optimal production costs of the power producers are calculated with the ramping cost included, considering a time horizon with N-1 contingency cases using contingency constrained optimal power flow (CCOPF), which is solved by the primal-dual interior point method (PDIPM). A contingency analysis is also performed taking into account the severity index of transmission line outages and its sensitivity analysis. The results from an illustrative case study based on the IEEE 30-bus system are analyzed. One attractive feature of the proposed approach is that an optimal solution is more realistic than the conventional approach because it satisfies physical constraints, such as the ramping constraint.

• Computers and Concrete
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• v.18 no.5
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• pp.983-998
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• 2016

Structural optimization is one of the most important topics in structural engineering and has a wide range of applicability. Therefore, the main objective of the present study is to apply the Lagrange Multiplier Method (LMM) for minimum cost design of singly and doubly reinforced rectangular concrete beams. Concrete and steel material costs are used as objective cost function to be minimized in this study, and ultimate flexural strength of the beam is considered to be as the main constraint. The ultimate limit state method with partial material strength factors and equivalent concrete stress block is used to derive general relations for flexural strength of RC beam and empirical coefficients are taken from topic 9 of the Iranian National Building Regulation (INBR9). Optimum designs are obtained by using the LMM and are presented in closed form solutions. Graphical representation of solutions are presented and it is shown that proposed design curves can be used for minimum cost design of the beams without prior knowledge of optimization and without the need for iterative trials. The applicability of the proposed relations and curves are demonstrated through two real life examples of SRB and DRB design situations and it is shown that the minimum cost design is actually reached using proposed method.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.10
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• pp.1561-1570
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• 1997

This study explores the treatment of the max-value cost function over a parameter interval in parametric optimization. To avoid the computational burden of the transformation treatment using an artificial variable, a direct treatment of the original max-value cost function is proposed. It is theoretically shown that the transformation treatment results in demanding an additional equality constraint of dual variables as a part of the Kuhn-Tucker necessary conditions. Also, it is demonstrated that the usability and feasibility conditions on the search direction of the transformation treatment retard convergence rate. To investigate numerical performances of both treatments, typical optimization algorithms in ADS are employed to solve a min-max steady-state response optimization. All the algorithm tested reveal that the suggested direct treatment is more efficient and stable than the transformation treatment. Also, the better performing of the direct treatment over the transformation treatment is clearly shown by constrasting the convergence paths in the design space of the sample problem. Six min-max transient response optimization problems are also solved by using both treatments, and the comparisons of the results confirm that the performances of the direct treatment is better than those of the tranformation treatment.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.7
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• pp.984-991
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• 2015

This paper presents the methodology for optimal design of power grid for offshore wind power plant (OWPP) and optimum location of offshore substation. The proposed optimization process is based on a genetic algorithm, where the objective cost model is composed of investment, power loss, repair, and reliability cost using the net present value during the whole OWPP life cycle. A probability wind power output is modeled to reflect the characteristics of a wind power plant that produces electricity through wind and to calculate the reliability cost called expected energy not supplied. The main objective is to find the minimum cost for grid connection topology by submarine cables which cannot cross each other. Cable crossing was set as a constraint in the optimization algorithm of grid topology of the wind power plant. On the basis of this method, a case study is conducted to validate the model by simulating a 100-MW OWF.

• Journal of Korea Multimedia Society
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• v.3 no.6
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• pp.633-642
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• 2000

This paper proposes a dominant source-based tree (DSBT) that constructs a localized multicast routing tree for dynamic multicasting without rerouting. To constrain end-to-end delays a multicast tree needs to be reconstructed when a new node joins the group due to additive tree constraint. In DSBT, a multicast group G is expressed by a (DS, NCM) pair, where DS is a dominant source address and NCM is a normalized cost margin. A node wishing to participate in a group selects a path that complies with NCM toward DS such that the end-to-end cost is constrained without any rerouting. Simulation results show that the proposed method performed better in terms of the overall tree cost compared with the Nave algorithm and in terms of the end-to-end delays between any two members compared with the Greedy algorithm.

• Journal of KIISE:Information Networking
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• v.29 no.4
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• pp.397-404
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• 2002

We propose a heuristic distributed unicast routing algorithm for minimizing the total cost of the path in a point to point network with do]ay constraint. The algorithm maintains a delay vector and a cost vector about the network states and finds the path using this information. In this paper, we show that our algorithm always finds a delay-constrained path if such a path exists and has O(│E│) message complexity(│E│is the number of links in the network). Also, simulation results show that the proposed algorithm has better cost performance than other delay-constrained routing algorithms.

• Journal of the Korea Convergence Society
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• v.11 no.1
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• pp.259-266
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• 2020

This study analyzes the effects of the obsolescence assets on the asymmetry of costs. Cost asymmetry refers to a lower percentage of costs when sales fall than increases in costs when sales increase. the obsolescence asset induces various decisions, including high maintenance costs and management improvements and replacement of facilities. This study is to analyze the cost behavior according to those decisions. The analysis showed that the higher the obsolescence of assets rate, we found cost elasticity, with a greater reduction in costs when sales decrease than the increase in costs when sales increase. Second, the lower the cost will not appear as the obsolescence of assets rate increases in case that the concentration of an item of property, plant and equipment is high, and when sales decrease. The above result means that the obsolescence of assets rate acts as operating risk and thus operates resources flexibly according to changes in sales, but when the concentration of property, plant and equipment is high, the decision-making constraint make it difficult for the flexible operation.

• Journal of Korean Society for Quality Management
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• v.18 no.2
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• pp.43-53
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• 1990

Mechanical components and structures are a major part of complex systems and the conseguences of their failure can be extremely costly. The ultimate goal of design engineers is to optimize these mechanical and structural design from the point of view of cost, reliability, weight, volume, maintainability and safety. An essential requirement of design optimization is to develop mathematical models for reliability at design stage. This paper is to minimize the cost of resources subject to the constraint that the reliability of the system must meet a specified level. The lagrange multiplier method is used to optimize the lognormal stress-lognormal strength problem. This optimization problem can be reduced to a search problem in one variable. A numerical example is presented to illustrate the optimization problem.

• Journal of Korean Society for Quality Management
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• v.35 no.4
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• pp.38-51
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• 2007

The House of Quality(HOQ) is used in the development stage to identify important customer attributes and corresponding engineering characteristics. The importance of each customer attribute obtained in the HOQ affects to the quality of the final product or service. Traditionally, such importance is derived based on the assumption that customer satisfaction is linearly proportional to the product performance. In this paper, we propose a nonlinear function so as to relate the product performance with the customer satisfaction according to the Kano model. A performance goal is obtained by maximizing the total customer satisfaction under a cost constraint and the importance of each customer attribute is developed from the performance goal. Therefore, the proposed approach incorporates the Kano categories and the improvement cost in determining the importance of customer attributes.