• Proceedings of the Korean Society for Quality Management Conference
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• 2006.11a
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• pp.133-138
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• 2006

The problem that we address is to determine the inventory stockage levels in a multi-echelon inventory system for repairable items in a multi-indenture system. We propose the simulation optimization approach to determine the stockage levels at each echelon, where a simulator for the underlying system is combined with an appropriate optimization tool, Genetic Algorithm (GA).

• Transactions of Materials Processing
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• v.18 no.2
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• pp.135-143
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• 2009

In the casting industry field, a lot of researches have been carried out to maximize soundness and productivity and improve quality of mass produced products. The researches on the optimum mould design by using computer simulation have achieved a lot of accomplishments in the die-casting process especially. Their results are utilized to mass-produce sound products in their field. But there are some difficulties to use the simulation in order to make the design of product and mould. In general, repetitive calculations of computer simulation require much analyzing time in order to make sound design of them. Another difficulty is that only expertise technicians can analyze results of the simulation. In order to solve such a problem, we are building mould design optimization system which consists of knowledge-based module, simulation, optimization module and interactive modeler(it is based on the commercial modeler). By using and interacting between these modules of that system, we can easily make an optimum design of mould and construct the database. This study introduce the general process of the system and connection method between the modules is mentioned above and some examples to apply it to real product.

• Journal of Korean Institute of Industrial Engineers
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• v.13 no.1
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• pp.61-67
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• 1987

A tool for optimizing simulated discrete variable stochastic systems, SIMICOM was developed and presented in [5]. In this paper an evaluation of its performance and results of comparisons with other popular methods for dealing with simulation-optimization problems will be provided. Based on several test problems it is concluded that SIMICOM dominates those methods.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2011.06a
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• pp.521-522
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• 2011

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.11a
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• pp.801-802
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• 2010

• Journal of Korean Institute of Industrial Engineers
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• v.33 no.2
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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.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.05a
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• pp.1086-1092
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• 2002

Computer simulation is essential to design the suspension elements of railway vehicle. By computer simulation, engineers can assess the feasibility of a given design factors and change them to get a better design. But if one wishes to perform complex analysis on the simulation, such as railway vehicle dynamic, the computational time can become overwhelming. Therefore, many researchers have used a mega model that has a regression model made by sampling data through simulation. In this paper, the neural network is used a mega model that have twenty-nine design variables and forty-six responses. After this mega model is constructed, multi-objective optimal solutions are achieved by using the differential evolution. This paper shows that this optimization method using the neural network and the differential evolution is a very efficient tool to solve the complex optimization problem.

• Journal of Information Processing Systems
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• v.18 no.6
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• pp.719-728
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• 2022

The prediction of short-term traffic flow is the theoretical basis of intelligent transportation as well as the key technology in traffic flow induction systems. The research on short-term traffic flow prediction has showed the considerable social value. At present, the support vector regression (SVR) intelligent prediction model that is suitable for small samples has been applied in this domain. Aiming at parameter selection difficulty and prediction accuracy improvement, the artificial bee colony (ABC) is adopted in optimizing SVR parameters, which is referred to as the ABC-SVR algorithm in the paper. The simulation experiments are carried out by comparing the ABC-SVR algorithm with SVR algorithm, and the feasibility of the proposed ABC-SVR algorithm is verified by result analysis. Continuously, the simulation experiments are carried out by comparing the ABC-SVR algorithm with particle swarm optimization SVR (PSO-SVR) algorithm and genetic optimization SVR (GA-SVR) algorithm, and a better optimization effect has been attained by simulation experiments and verified by statistical test. Simultaneously, the simulation experiments are carried out by comparing the ABC-SVR algorithm and wavelet neural network time series (WNN-TS) algorithm, and the prediction accuracy of the proposed ABC-SVR algorithm is improved and satisfactory prediction effects have been obtained.

• International conference on construction engineering and project management
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• 2015.10a
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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.

• Journal of the Korean Society of Marine Environment & Safety
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• v.23 no.3
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• pp.258-265
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• 2017

This paper validates a system identification method using mathematical optimization using sea trial measurement data as a benchmark. A fast time simulation tool, SIMOPT, and a Rheinmetall Defence mathematical model have been adopted to conduct initial hydrodynamic coefficient estimation and simulate ship modelling. Calibration for the environmental effect of sea trial measurement and sensitivity analysis have been carried out to enable a simple and efficient optimization process. The optimization process consists of three steps, and each step controls different coefficients according to the corresponding manoeuvre. Optimization result of Step 1, an optimization for coefficient on x-axis, was similar compared to values applying an empirical regression formulae by Clarke and Norrbin, which is used for SIMOPT. Results of Steps 2 and 3, which are for linear coefficients and nonlinear coefficients, respectively, was differ from the calculation results of the method by Clarke and Norrbin. A comparison for ship trajectory of simulation results from the benchmark and optimization results indicated that the suggested stepwise optimization method enables a coefficient tuning in a mathematical way.