• 한국수자원학회논문집
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• 제46권4호
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• pp.373-387
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• 2013

수자원시스템의 효율적인 운영 및 관리를 위해서는 하천 시설물들을 효율적으로 연계운영 할 필요가 있다. 그러나 이를 위한 시뮬레이션 모형은 최선의 대안을 보장하지 못하고, 최적화 모형은 복잡한 수계 현황을 유연하게 고려하는데 어려움이 있다. 따라서 시뮬레이션과 최적화 기법의 한계점을 서로 보완해서 활용하는 것이 바람직하다. 이에 본 연구에서는 시뮬레이션과 최적화 기법의 원론적 비교를 통해 각 기법의 장 단점을 분석하고, 두 방법의 한계점을 극복할 수 있는 시뮬레이션 기반의 최적화 모형, CoWMOM의 활용을 제안한다. 아울러 댐-보 연계운영 모형의 활용방안으로 i) 과거의 특정 기간에 대한 분석 도구로써의 활용법과, ii) 미래 수문 정보가 불확실한 상황에서 댐-보 연계운영을 하는 현실에 적합한 모형 활용 절차를 제시한다.

• Nuclear Engineering and Technology
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• 제52권5호
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• pp.956-963
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• 2020

Dose optimization for Radioactive Occupational Personal (ROP) is an important subject in nuclear and radiation safety field. The geometric environment of a nuclear facility is complex and the work area is radioactive, so traditional navigation model and radioactive data field cannot form an effective environment model for dose assessment and dose optimization. The environment model directly affects dose assessment and indirectly affects dose optimization, this is an urgent problem needed to be solved. Therefore, this paper focuses on an environment model used for Dose Assessment and Dose Optimization (DA&DO). We designed a multi-layer radiation field coupling modeling method, and then explored the influence of the environment model to DA&DO by virtual simulation. Then, a simulation test is done, the multi-layer radiation field coupling model for nuclear facilities is demonstrated to be effective for dose assessment and dose optimization through the experiments and analysis.

• 국제학술발표논문집
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• The 6th International Conference on Construction Engineering and Project Management
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• pp.221-225
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• 2015

To hoist construction workers to their working space is directly related to the productivity of building construction since hoisting tasks are carried out during the working time. In order to reduce hoisting time in the condition that the number of construction lift-cars is limited, various types of the lift-cars group operation plans such as zoning and sky-lobby have been applied. However, previous researches on them cannot be compared in the performance due to their methodological limitation, discrete-event simulation methods, and cannot be find better solution to increase the performance. Therefore, this research proposed the simulation-based optimization model combining the agent-based simulation method to the scatter search optimization methods. Using the proposed model, this paper carried out the comparison analysis on the performance of typical operation plans and also optimize an operation plans by controlling the service range of lift-cars, the size and number of service zones. In this case study, it is verified that better alternatives than typical operation plans can be exists and it is possible to increase the productivity of building construction.

• 한국CDE학회논문집
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• 제17권5호
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• pp.375-386
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• 2012

Most engineering design problems require analyses or simulations to evaluate objective functions. However, a single simulation can take many hours or even days to finish for many real world problems. As a result, design optimization becomes impossible since they require hundreds or thousands of simulation evaluations. The surrogate-based optimization (SBO) strategy became a remedy for such computationally expensive analyses and simulations. A surrogate-based optimization strategy has been developed in this study in order to improve global optimization performance. The strategy is a heuristic algorithm and it exploits not only multiple surrogates, but also multiple optimizers. Multiple optimizations of multiple surrogate models yield multiple candidate design points of optima. During the sequential sampling process, the algorithm ranks candidate design points, selects the points as many as specified, and builds the improved surrogate model. Various mathematical functions with different numbers of design variables are chosen to compare the proposed method with the other most recent algorithm, MSEGO. The proposed method shows superior performance to the other method.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1990년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 26-27 Oct. 1990
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• pp.240-245
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• 1990

A on-line optimization scheme based on model in a binary distillation process is proposed. A reduced-order model utilized the concept of collocation is used as a process model and the recursive prediction error method is employed to identify the reduced-order model. The concentrations of end products are controlled by nonlinear adaptive predictive control algorithm. The objective function is constructed to find optimum operate condition for saving utility cost. The proposed optimization is scheme is tested through simulation studies in 13-staged water-methanol distillation column.

• 산업경영시스템학회지
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• 제40권4호
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• pp.211-220
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• 2017

The application of the theoretical model to real assembly lines has been one of the biggest challenges for researchers and industrial engineers. There should be some realistic approach to achieve the conflicting objectives on real systems. Therefore, in this paper, a model is developed to synchronize a real system (A discrete event simulation model) with a theoretical model (An optimization model). This synchronization will enable the realistic optimization of systems. A job assignment model of the assembly line is formulated for the evaluation of proposed realistic optimization to achieve multiple conflicting objectives. The objectives, fluctuation in cycle time, throughput, labor cost, energy cost, teamwork and deviation in the skill level of operators have been modeled mathematically. To solve the formulated mathematical model, a multi-objective simulation integrated hybrid genetic algorithm (MO-SHGA) is proposed. In MO-SHGA each individual in each population acts as an input scenario of simulation. Also, it is very difficult to assign weights to the objective function in the traditional multi-objective GA because of pareto fronts. Therefore, we have proposed a probabilistic based linearization and multi-objective to single objective conversion method at population evolution phase. The performance of MO-SHGA is evaluated with the standard multi-objective genetic algorithm (MO-GA) with both deterministic and stochastic data settings. A case study of the goalkeeping gloves assembly line is also presented as a numerical example which is solved using MO-SHGA and MO-GA. The proposed research is useful for the development of synchronized human based assembly lines for real time monitoring, optimization, and control.

• Journal of Information Processing Systems
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• 제18권5호
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• pp.665-676
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• 2022

In modern logistics, the effective use of the vehicle volume and loading capacity will reduce the logistic cost. Many heuristic algorithms can solve this knapsack problem, but lots of these algorithms have a drawback, that is, they often fall into locally optimal solutions. A fusion optimization method based on simulated annealing algorithm (SA) and binary particle swarm optimization algorithm (BPSO) is proposed in the paper. We establish a logistics knapsack model of the fusion optimization algorithm. Then, a new model of express logistics simulation system is used for comparing three algorithms. The experiment verifies the effectiveness of the algorithm proposed in this paper. The experimental results show that the use of BPSO-SA algorithm can improve the utilization rate and the load rate of logistics distribution vehicles. So, the number of vehicles used for distribution and the average driving distance will be reduced. The purposes of the logistics knapsack problem optimization are achieved.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2011년도 제42회 하계학술대회
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• pp.187-188
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• 2011

This paper proposes the hybrid Complex-PSO algorithm based on the complex search method and particle swarm optimization (PSO) for unconstrained optimization. This hybridization intends to produce faster and more accurate convergence to the optimum value. These hybrid will concentrate on determining the dynamic load model parameters, the ZIP model and induction motor model parameters. Measurement-based parameter estimation, which employs measurement data to derive load model parameters, is used. The theoretical foundation of the measurement-based approach is system identification. The main objective of this paper is to demonstrate how the standard particle swarm optimization and complex method can be improved through hybridization of the two methods and the results will be compared with that of their original forms.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2017년도 학술발표회
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• pp.184-184
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• 2017

A nation-wide water-energy-food (WEF) nexus simulation model has been developed by the authors and successfully applied to South Korea to predict the sustainability of those three resources in the next 30 years. The model was also capable of simulating future scenarios of resources allocation based on priority rules aiming to maximize resources sustainability. However, the process was still relying on several assumptions and trial-and-error approach, which sometimes resulted in non-optimal solutions of resources allocation. In this study, an optimization module was introduced to enhance the model in generating optimal resources management rules. The objective of the optimization was to maximize the reliability index of resources by determining the resources' allocation and/or priority rules for each demand type that accordingly reflect the resources management policies. Implementation of the optimization module would result in balanced allocation and management of limited resources and assist the stakeholders in deciding resources' management plans, either by fulfilling the domestic production or by global trading.

• 대한산업공학회지
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• 제33권2호
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• pp.282-289
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• 2007

While demands for express couriers service are rapidly increasing due to recent progress of electronic commerce, express courier service companies are struggling to take a larger market share through ongoing improvement in their service processes. Cut-off time is the time limit that all orders delivered before the limit are guaranteed for the delivery within the very next day. Extending cut-off time for express service centers can provide the express company with increase of total sales, but it may also cause increasing the possibility not to satisfy customer needs due to work delay in the consolidation terminal. We develop a design model for express courier service network based on a recursive optimization/simulation procedure. With the optimization model, we seek key design parameters such as the cut-off time for express service centers and the capacity of the consolidation terminal maximizing total sales profit while satisfying the desired level of performances. With the simulation model, we consider the dynamic nature of the network and obtain relationships between the design parameters and the performance measures with the multiple linear regression. The validity of the model is examined with an example.