• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권9호
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• pp.4329-4348
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• 2019

Mobile cloud computing (MCC) can offload heavy computation from mobile devices onto nearby cloudlets or remote cloud to improve the performance as well as to save energy for these devices. Therefore, it is essential to consider how to achieve efficient computation offloading with constraints for multiple users. However, there are few works that aim at multi-objective problem for multiple users. Most existing works concentrate on only single objective optimization or aim to obtain a tradeoff solution for multiple objectives by simply setting weight values. In this paper, a multi-objective optimization model is built to minimize the average energy consumption, time and cost while satisfying the constraint of bandwidth. Furthermore, an improved multi-objective optimization algorithm called D-NSGA-II-ELS is presented to get Pareto solutions with better convergence and diversity. Compared to other existing works, the simulation results show that the proposed algorithm can achieve better performance in terms of energy consumption, time and cost while satisfying the constraint of the bandwidth.

• Nuclear Engineering and Technology
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• 제55권6호
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• pp.2222-2229
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• 2023

Radon and radon progeny being natural radioactive pollutants, seriously affect the health of uranium miners. Radon reduction by ventilation is an essential means to improve the working environment. Firstly, the relational model is built between the radon exhalation rate of the loose body and the ventilation parameters in the stope with radon percolation-diffusion migration dynamics. Secondly, the model parameters of radon exhalation dynamics are uncertain and described by triangular membership functions. The objective functions of the left and right equations of the radon exhalation model are constructed according to different possibility levels, and their extreme value intervals are obtained by the immune particle swarm optimization algorithm (IPSO). The fuzzy target and fuzzy constraint models of radon exhalation are constructed, respectively. Lastly, the fuzzy aggregation function is reconstructed according to the importance of the fuzzy target and fuzzy constraint models. The optimal control decision with different possibility levels and importance can be obtained using the swarm intelligence algorithm. The case study indicates that the fuzzy aggregation function of radon exhalation has an upward trend with the increase of the cut set, and fuzzy optimization provides the optimal decision-making database of radon treatment and prevention under different decision-making criteria.

• Biotechnology and Bioprocess Engineering:BBE
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• 제10권5호
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• pp.408-417
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• 2005

Increasing numbers of value added chemicals are being produced using microbial fermentation strategies. Computational modeling and simulation of microbial metabolism is rapidly becoming an enabling technology that is driving a new paradigm to accelerate the bioprocess development cycle. In particular, constraint-based modeling and the development of genome-scale models of industrial microbes are finding increasing utility across many phases of the bioprocess development workflow. Herein, we review and discuss the requirements and trends in the industrial application of this technology as we build toward integrated computational/experimental platforms for bioprocess engineering. Specifically we cover the following topics: (1) genome-scale models as genetically and biochemically consistent representations of metabolic networks; (2) the ability of these models to predict, assess, and interpret metabolic physiology and flux states of metabolism; (3) the model-guided integrative analysis of high throughput 'omics' data; (4) the reconciliation and analysis of on- and off-line fermentation data as well as flux tracing data; (5) model-aided strain design strategies and the integration of calculated biotransformation routes; and (6) control and optimization of the fermentation processes. Collectively, constraint-based modeling strategies are impacting the iterative characterization of metabolic flux states throughout the bioprocess development cycle, while also driving metabolic engineering strategies and fermentation optimization.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 1994년도 춘계공동학술대회논문집; 창원대학교; 08월 09일 Apr. 1994
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• pp.103-111
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• 1994

An interactive and iterative design method based on the constraint satisfaction problem (CSP) technique was developed to generate an ergonomically sound layout of a control panel. This control panel layout method attempts to incorporate a variety of relevant ergonomic principles and design constraints, and generate an optimal or, at least, a "satisfactory" solution through iterative interactions with the designer. The existing panel design and layout methods are mostly based on the optimization of single objective function formulated to reflect and trade off all ergonomic design objectives which are largely different in their nature. In fact, the problem of seeking an ergonomically sound panel design should be viewed as a multiple objective optimization problem. Furthermore, most of the design objectives should be understood as constraints rather than objectives to be optimized. Hence, a constraint satisfaction approach is proposed in this study as a framework for the panel designer to search through the design decision space effectively and make various design decisions iteratively. In order to apply the constraint satisfaction approach to the panel design procedure, the ergonomic principles such as frequency-of-use, importance, functional grouping, and sequence-of-use are formalized as CSP terms. With this formalization, a prototype system was implemented and applied to panel layout problems. The results clearly showed the effectiveness of the proposed approach since it permits designers to consider and iteratively evaluate various design constraints and ergonomic principles, and, therefore, aids the panel designer to come up with an ergonomically sound control panel layout.

• Structural Engineering and Mechanics
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• 제65권6호
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• pp.707-719
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• 2018

In this article, a new method is introduced to improve the local search capability of meta-heuristic algorithms using the projection of the path on the border of constraints. In a mathematical point of view, the Gradient Projection Method is applied through a new approach, while the imposed limitations are removed. Accordingly, the gradient vector is replaced with a new meta-heuristic based vector. Besides, the active constraint identification algorithm, and the projection method are changed into less complex approaches. As a result, if a constraint is violated by an agent, a new path will be suggested to correct the direction of the agent's movement. The presented procedure includes three main steps: (1) the identification of the active constraint, (2) the neighboring point determination, and (3) the new direction and step length. Moreover, this method can be applied to some meta-heuristic algorithms. It increases the chance of convergence in the final phase of the search process, especially when the number of the violations of the constraints increases. The method is applied jointly with the authors' newly developed meta-heuristic algorithm, entitled Star Graph. The capability of the resulted hybrid method is examined using the optimal design of truss and frame structures. Eventually, the comparison of the results with other meta-heuristics of the literature shows that the hybrid method is successful in the global as well as local search.

• 제어로봇시스템학회논문지
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• 제21권7호
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• pp.595-601
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• 2015

This paper presents an unified chassis control with electronic stability control (ESC) and active front steering (AFS) under lateral force constraint on AFS. When generating the control yaw moment, an optimization problem is formulated in order to determine the tire forces, generated by ESC and AFS. With Karush-Kuhn-Tucker optimality condition, the optimum tire forces can be algebraically calculated. On low friction road, the lateral force in front wheels is easily saturation. When saturated, AFS cannot generate the required control yaw moment. To cope with this problem, new constraint on the lateral tire force is added into the original optimization problem. To check the effectiveness of the propose method, simulation is performed on the vehicle simulation package, CarSim.

• 한국정보처리학회논문지
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• 제6권2호
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• pp.439-448
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• 1999

본 논문에서는 신경회로망과 유전자 알고리즘을 이용하여 셀룰러 무선채널 할당을 위한 최적화 알고리즘을 제안하였다. 채널할당 과정을 채널할당 문제에 내포된 제한사항들을 나타내는 에너지함수의 최소화 과정으로 규정하였다. 채널간, 인접채널, 사이트간의 세 가지 제한사항이 고려되었다. 최적의 채널할당을 위하여 신경회로망을 이용한 방식에서는 강제적인 채널 할당 및 셀 순서 변화 등의 기법이 개발되었고 유전자 알고리즘 방식에서는 자료구조와 적절한 유전연산자를 개발하였다. 실험결과로서, 두 최적화 방법의 채널할당률을 나타내었고 그 결과들을 비교하였다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.1362-1366
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• 2003

Workload programming is allocating suitable workloads of production process according to the needs of products, which would minimize the total cost of both work and stock under some constraint conditions. In this paper, a production process flow chart of discrete manufacturing is presented by a Petri net, and the optimization model of workload-stock is established. An approach of the optimal workloads is provided by means of the integer matrix theory. An example is given to verify this method.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년도 제37회 하계학술대회 논문집 A
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• pp.8-9
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• 2006

This paper presents a new methodology to calculate an optimal solution of equilibrium to power system differential algebraic equations. It employs a nonlinear interior point method for solving the optimization formulation, which includes dynamic equations representing two-axis synchronous generator models with AVR and speed governing control, algebraic equations, and steady-state nonlinear loads. Equilibrium optimization (EOPT) is useful for diverse purposes in power system analysis and control with consideration of the system frequency constraint.

• Communications for Statistical Applications and Methods
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• 제6권1호
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• pp.143-150
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• 1999

Ko(1998) proposed a procedure to enhance the efficiency of double sampling plans by allowing second-stage sample size and critical region to depend on first-stage evidence using constraint optimization approaches. In this study further developments of such plans by incorporating several practically possible researcher's aims into the optimization are considered. Comparisons are made with the optimal ordinary double sampling plan and also among them It is observed that it is to some extent possible to match the details of the optimization to certain qualitative methodological aims.