• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.10
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• pp.4864-4882
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• 2016

In this work, we consider the optimization problem of minimizing energy consumption for real-time multicast over wireless multi-hop networks. Previously, a distributed primal-dual subgradient algorithm was used for finding a solution to the optimization problem. However, the traditional subgradient algorithms have drawbacks in terms of i) sensitivity to iteration parameters; ii) need for saving previous iteration results for computing the optimization results at the current iteration. To overcome these drawbacks, using a joint network coding and scheduling optimization framework, we propose a novel distributed primal-dual Random Deflected Subgradient (RDS) algorithm for solving the optimization problem. Furthermore, we derive the corresponding recursive formulas for the proposed RDS algorithm, which are useful for practical applications. In comparison with the traditional subgradient algorithms, the illustrated performance results show that the proposed RDS algorithm can achieve an improved optimal solution. Moreover, the proposed algorithm is stable and robust against the choice of parameter values used in the algorithm.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.31 no.3
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• pp.287-295
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• 1995

fishing boat is a specialized vessel which is intended to perform certain well defined tasks. Its size, deck-layout, carrying capacity and equipment are all related to its function in carrying out its planned operations. Therefore the process of fishing boat design is inherently combined with optimization of the design variables called the economic optimization criteria. Optimization then is a process in which minimum value of weight or cost is established through evaluation of consecutive designs in which one or more design parameters are varied. This paper is to study the basic-design of Stow-net fishing vessel in the Mok-Po region. The main task is developed the preliminary design model of engineering economic system in order to use optimization techniques from operation research the design problem needs to be expressed in terms of objective function and numerous constrains like : speed, fish hold capacity, fishing range, displacement and weight, ratio of main dimensions, etc. The objective function represents the criterion which is NPV such as the ratio of revene/cost. When using computers of limited capacity like P/C, the developed basic-design model of the economic optimization procedure must be simplified to V, Cb, L/B, Dv, Db and less than 15 constraint equations. The main conclusions of this study have attempted to show that economic considerations are essential in Stow-net fishing vessel basic design and operations, and that techno-economic evaluation is an important tool for the design of Stow-net fishing vessel in 69ton and 79ton.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2008.03a
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• pp.247-254
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• 2008

The primary objective of this research is to develop an efficient design and optimization methodology for SRM Wagon Wheel Grain and to develop of software for practical designing and optimization of Wagon Wheel grains. This work will provide a design process reference guide for engineers in the field of Solid Rocket Propulsion. Using these proposed design methods, SRM Wagon Wheel grains can be designed for various geometries, their optimal solutions can be found and best possible configuration be attained thereby ensuring finest design in least possible iterations & time. The main focus is to improve computational efficiency at various levels of the design work. These have been achieved by the following way. a. Evaluation of system requirements and design objectives. b. Development of Geometric Model of Wagon Wheel grain configuration. c. Internal ballistic performance predictions. d. Preliminary designing of the Wagon Wheel grain configuration involving various independent geometric variables. e. Optimization of the grain configuration using Sequential Quadratic Programming f. In depth analysis of the optimal results considering affects of various geometric variables on ballistic parameters and analysis of performance prediction outputs have been performed g. Development of software for design and optimization of Wagon Wheel Grain. By using these proposed design methods, SRM Wagon Wheel grains can be designed by using geometric model, their optimal solutions can be found and best possible configuration be attained thereby ensuring finest design.

• Nuclear Engineering and Technology
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• v.53 no.11
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• pp.3665-3674
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• 2021

One of the important parts of the in-core fuel management is loading pattern optimization (LPO). The loading pattern optimization as a reasonable design of the in-core fuel management can improve both economic and safe aspects of the nuclear reactor. This work proposes the hybrid of fuzzy logic controller with harmony search algorithm (HS) for loading pattern optimization in a pressurized water reactor. The music improvisation process to find a pleasing harmony is inspiring the harmony search algorithm. In this work, the adjustment of the harmony search algorithm parameters such as the bandwidth and the pitch adjustment rate are increasing performance of the proposed algorithm which is done through a fuzzy logic controller. Hence, membership functions and fuzzy rules are designed to improve the performance of the HS algorithm and achieve optimal results. The objective of the method is finding an optimum core arrangement according to safety and economic aspects such as reduction of power peaking factor (PPF) and increase of effective multiplication factor (Keff). The proposed approach effectiveness has been tried in two cases, Michalewicz's bivariate function problem and NEACRP LWR core. The results show that by using fuzzy harmony search algorithm the value of the fitness function is improved by 15.35%. Finally, with regard to the new solutions proposed in this research it could be used as a trustworthy method for other optimization issues of engineering field.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.608-615
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• 2022

Construction projects are large-scale projects that require extensive construction costs and resources. Especially, scheduling is considered as one of the essential issues for project success. However, the schedule and resource management are challenging to conduct in high-tech construction projects including complex design of MEP and architectural finishing which has to be constructed within a limited workspace and duration. In order to deal with such a problem, this study suggests resource and sequence optimization using constraint programming in construction projects. The optimization model consists of two modules. The first module is the data structure of the schedule model, which consists of parameters for optimization such as labor, task, workspace, and the work interference rate. The second module is the optimization module, which is for optimizing resources and sequences based on Constraint Programming (CP) methodology. For model validation, actual data of plumbing works were collected from a construction project using a five-minute rate (FMR) method. By comparing actual data and optimized results, this study shows the possibility of reducing the duration of plumbing works in construction projects. This study shows decreased overall project duration by eliminating work interference by optimizing resources and sequences within limited workspaces.

• Steel and Composite Structures
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• v.47 no.6
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• pp.759-779
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• 2023

The paper proposes two hybrid metaheuristic optimization and artificial neural network (ANN) methods for the close prediction of the ultimate axial compressive capacity of concentrically loaded concrete filled double skin steel tube (CFDST) columns. Two metaheuristic optimization, namely genetic algorithm (GA) and particle swarm optimization (PSO), approaches enable the dynamic training architecture underlying an ANN model by optimizing the number and sizes of hidden layers as well as the weights and biases of the neurons, simultaneously. The former is termed as GA-ANN, and the latter as PSO-ANN. These techniques utilize the gradient-based optimization with Bayesian regularization that enhances the optimization process. The proposed GA-ANN and PSO-ANN methods construct the predictive ANNs from 125 available experimental datasets and present the superior performance over standard ANNs. Both the hybrid GA-ANN and PSO-ANN methods are encoded within a user-friendly graphical interface that can reliably map out the accurate ultimate axial compressive capacity of CFDST columns with various geometry and material parameters.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.39 no.8
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• pp.792-804
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• 1990

This paper describes an efficient optimization algorithm by calculating sensitivity function for power system stabilization. In power system, the dynamic performance of exciter, governor etc. following a disturbance can be presented by a nonlinear differential equation. Since a nonlinear equation can be linearized for small disturbances, the state equation is expressed by a system matrix with system parameters. The objective function for power system operation will be related to the system parameter and the initial state at the optimal control condition for control or stabilization. The object function sensitivity to the system parameter can be considered to be effective in selecting the optimal parameter of the system.

• Transactions of Materials Processing
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• v.9 no.5
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• pp.526-532
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• 2000

Springback simulation is receiving increasing attention throughout the automotive industry and the academic world. The knowledge of the real springback of stamped parts can help the stamping technicians to modify the process parameters or die geometry in order to reduce the shape defect. This paper presents the results of springback simulation after aluminium square cup deep drawing and trimming simulation, and results of springback optimization using response surface method.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.82-87
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• 1994

In this study, dynamic optimal design far a two degree-of-freedom anthropomorphic robot module is performed. Several dynamic design indices associated with the inertia matrix and the inertia power array are introduced. Analysis for the relationship between the dynamic parameters and the design indices shows that trade-offs exist between the isotropy and the dynamic design indices related to the actuator size. A composite design index is employed to deal with multi-criteria based design with different weighting factors, in a systematic manner. We demonstrate the fact that dynamic optimization is another significant step to enhance the system performances, followed by kinematic optimization.

• Proceedings of the IEEK Conference
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• 2003.07a
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• pp.477-480
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• 2003

Packet losses in the Internet can dramatically degrade quality of multimedia streams. Forward Error Correction (FEC) is one of the best methods that can protect data from packet erasures by means of sending additional redundant information. Proposed control algorithm provides the possibility of receiving real-time multimedia streams of given quality wifth minimal traffic overhead. The traffic optimization is reached by adjusting packet size as well as block code parameters. Calculations and simulation results show that for non-bursty network conditions traffic optimization can lead to more than 50% bandwidth reduction.