• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.13-13
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• 2000

This paper considers delay-dependent guaranteed cost control for uncertain time-delay systems with norm-bounded parametric uncertainties. A new delay-dependent condition for the existence of the guaranteed cost control law is presented in terms of linear matrix inequalities (LMI). An algorithm involving convex optimization is proposed to design a controller which guarantees the suboptimal minimum of the guaranteed cost of the closed-loop system for all admissible uncertainties.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2001년도 춘계학술대회논문집D
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• pp.286-291
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• 2001

This paper describes an optimal scheduling for ice slurry systems for energy cost saving. The optimization technique applied in the study is the dynamic programming method, for which the state variable is the storage in the ice storage tank and the control variable is the state of chiller's on-off switching. Though the costs during charge period is included in optimization by taking the average cost of ice per hour for slurry making, the time horizon for the simulation is limited building cooling period because accurate charge rate from the ice maker into the ice storage tank cannot be estimated during the charge period. In the operating simulation after optimizing procedure, energy consumption and operating cost for the optimal control are calculated and compared with them for a conventional control with one case of cooling load profile.

• 제어로봇시스템학회논문지
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• 제16권5호
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• pp.476-480
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• 2010

This study deals with stockout costs in the supply chain optimization model under the framework of batch-storage network. Stockout is very popular in chemical industries. Estimating stockout cost involves an understanding of customer reactions to a seller being out of stock at the time the customer wants to buy an item. This involves massively non-trivial work such as direct customer interviews and extensive mail survey. In this study, we will introduce a new interpretation of stockout costs combined with batchstorage network optimization model and thus suggest an easy way of estimating stockout costs. Optimization model suggest that optimal process and storage sizes considering stockout cost are smaller than those that do not consider stockout cost. An illustrative example support the analytical results.

• 대한산업공학회지
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• 제30권3호
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• pp.250-260
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• 2004

This study considers a linear connected-(r,s)-out-of-(m,n):F lattice system whose components are ordered like the elements of a linear (m,n )-matrix. We assume that all components are in the state 1 (operating) or 0 (failed) and identical and s-independent. The system fails whenever at least one connected (r,s)-submatrix of failed components occurs. The purpose of this paper is to present an optimization scheme that aims at minimizing the expected cost per unit time. To find the optimal threshold of maintenance intervention, we use a genetic algorithm for the cost optimization procedure. The expected cost per unit time is obtained by Monte Carlo simulation. The sensitivity analysis to the different cost parameters has also been made.

• Journal of Information Processing Systems
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• 제17권3호
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• pp.615-629
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• 2021

With the development of mobile edge computing, how to utilize the computing power of edge computing to effectively and efficiently offload data and to compute offloading is of great research value. This paper studies the computation offloading problem of multi-user and multi-server in mobile edge computing. Firstly, in order to minimize system energy consumption, the problem is modeled by considering the joint optimization of the offloading strategy and the wireless and computing resource allocation in a multi-user and multi-server scenario. Additionally, this paper explores the computation offloading scheme to optimize the overall cost. As the centralized optimization method is an NP problem, the game method is used to achieve effective computation offloading in a distributed manner. The decision problem of distributed computation offloading between the mobile equipment is modeled as a multi-user computation offloading game. There is a Nash equilibrium in this game, and it can be achieved by a limited number of iterations. Then, we propose a distributed computation offloading algorithm, which first calculates offloading weights, and then distributedly iterates by the time slot to update the computation offloading decision. Finally, the algorithm is verified by simulation experiments. Simulation results show that our proposed algorithm can achieve the balance by a limited number of iterations. At the same time, the algorithm outperforms several other advanced computation offloading algorithms in terms of the number of users and overall overheads for beneficial decision-making.

• 대한기계학회논문집A
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• 제30권8호
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• pp.889-896
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• 2006

The concept of reliability has been applied to the topology optimization based on a reliability index approach or a performance measure approach. Since these approaches, called double-loop single vector approach, require the nested optimization problem to obtain the most probable point in the probabilistic design domain, the time for the entire process makes the practical use infeasible. In this work, new reliability-based topology optimization method is proposed by utilizing single-loop single-vector approach, which approximates searching the most probable point analytically, to reduce the time cost. The results of design examples show that the proposed method provides efficiency curtailing the time for the optimization process and accuracy satisfying the specified reliability.

• International Journal of Computer Science & Network Security
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• 제22권10호
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• pp.113-130
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• 2022

Sophisticated automation-based electronics world, more electrical and electronic devices are being used by people from different regions across the universe. Different manufacturers and vendors develop and market a wide variety of power generation and utilization devices under different operating parameters and conditions. People use a variety of appliances which use electrical energy as power source. These appliances or gadgets utilize the generated energy in different ratios. Night time the utilization will be less when compared with day time utilization of power. In industrial areas especially mechanical industries or Heavy machinery usage regions power utilization will be a diverse at different time intervals and it vary dynamically. This always causes a fluctuation in the grid lines because of the random and intermittent use of these apparatus while the power generating apparatus is made to operate to provide a steady output. Hence it necessitates designing and developing a method to optimize the power generated and the power utilized. Lot of methodologies has been proposed in the recent years for effective optimization and economical load dispatch. One such technique based on intelligent and evolutionary based is Black Widow Optimization BWO. To enhance the optimization level BWO is hybridized. In this research BWO based optimize the load for multi area is proposed to optimize the cost function. A three type of system was compared for economic loads of 16, 40, and 120 units. In this research work, BWO is used to improve the convergence rate and is proven statistically best in comparison to other algorithms such as HSLSO, CGBABC, SFS, ISFS. Also, BWO algorithm best optimize the cost parameter so that dynamically the load and the cost can be controlled simultaneously and hence effectively the generated power is maximum utilized at different time intervals with different load capacity in different regions of utilization.

• Structural Engineering and Mechanics
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• 제45권2호
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• pp.211-232
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• 2013

In this study a multi-objective optimization problem is solved. The objectives used here include simultaneous minimum construction cost in term of sections weight, minimum structural damage using a damage index, and minimum non-structural damage in term of inter-story drift under the applied ground motions. A high-speed and low-error neural network is trained and employed in the process of optimization to estimate the results of non-linear time history analysis. This approach can be utilized for all steel or concrete frame structures. In this study, the optimal design of a planar eccentric braced steel frame is performed with great detail, using the presented multi-objective algorithm with a discrete population and then a moment resisting frame is solved as a supplementary example.

• 한국산학기술학회논문지
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• 제17권4호
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• pp.19-25
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• 2016

사회기반시설물을 포함한 구조물은 수명유지 또는 연장을 위하여 적절한 점검과 유지보수가 필수적이다. 이러한 점검과 유지보수는 일반적으로 생애주기비용 평가를 통해 관련 계획이 수립된다. 본 논문에서는 구조물의 생애주기비용과 그 사용으로 인해 발생되는 이익을 고려하는 확률론적 비용-이익분석과 이를 통한 구조물 최적수명 결정 방법을 다루고자 한다. 생애주기비용은 구조물 초기 제작/건설비용, 유지보수 비용과 구조물 파괴로 인한 예상손실을 고려하게 된다. 일반적으로 구조물의 수명연장은 생애주기비용의 증가를 유발하나 사용기간 증가로 인해 발생되는 이익 또한 증가하여, 이를 최적화하는 수명관리에 관심을 가질 필요가 있다. 생애주기 평가에 있어서 유지보수 적용이 구조성능, 구조물 파괴확률 그리고 수명에 미치는 영향을 확률론적 방법을 적용하여 평가하며, 이를 통해 생애주기비용과 이익의 차이를 목적함수로 구성하게 된다. 이 목적함수가 최대가 되는 지점이 설계변수인 구조물 최적수명이 되는데, 최적화문제 구성에 있어서 제한조건의 변화에 따라 유지보수 계획수립도 가능하다. 본 논문에서 다루어지는 구조물 수명관리 최적화기법이 안전성과 효율성을 동시에 고려하는 사회기반시설물 수명관리에 기여할 것으로 기대한다.

• 유통과학연구
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• 제14권2호
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• pp.41-45
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• 2016

Purpose - Finding an optimal path is an essential component for the design and operation of smart transportation or logistics network. Many applications in navigation system assume that travel time of each link is fixed and same. However, in practice, the travel time of each link changes over time. In this paper, we introduce a new transportation problem to find a latest departing time and delivery path between the two nodes, while not violating the appointed time at the destination node. Research design, data, and methodology - To solve the problem, we suggest a mathematical model based on network optimization theory and a backward search method to find an optimal solution. Results - First, we introduce a dynamic transportation problem which is different with traditional shortest path or minimum cost path. Second, we propose an algorithm solution based on backward search to solve the problem in a large-sized network. Conclusions - We proposed a new transportation problem which is different with traditional shortest path or minimum cost path. We analyzed the problem under the conditions that travel time is changing, and proposed an algorithm to solve them. Extending our models for visiting two or more destinations is one of the further research topics.