• Journal of the Korean Operations Research and Management Science Society
• /
• v.30 no.1
• /
• pp.43-54
• /
• 2005

A flexible assembly line (FAL) is a production system that assembles various parts in unidirectional flow line with many constraints and manufacturing flexibilities. In this research we deal with a FAL balancing problem with the objective of minimizing the maximum workload allocated to the stations. However, almost all the existing researches do not appropriately consider various constraints due to the problem complexity. Therefore, this study addresses a balancing problem of FAL with many constraints and manufacturing flexibilities, unlike the previous researches. We use a genetic algorithm (GA) to solve this problem. To apply GA to FAL. we suggest a genetic representation suitable for FAL balancing and devise evaluation method for individual's fitness and genetic operators specific to the problem, including efficient repair method for preserving solution feasibility. After we obtain a solution using the proposed GA. we use a heuristic method for reassigning some tasks of each product to one or more stations. This method can improve workload smoothness and raise work efficiency of each station. The proposed algorithm is compared and analyzed in terms of solution quality through computational experiments.

• Journal of the Korean Society for Precision Engineering
• /
• v.34 no.2
• /
• pp.133-138
• /
• 2017

Inverter-Type refrigerators are known to consume less energy by varying the inverter frequency according to indoor temperatures and refrigerant pressure through indoor-outdoor communication. However, many commercial operators cannot afford to replace indoor units with ones capable of communication. In a non-communication configuration, indoor units are connected with an inverter-type outdoor unit without intercommunication abilities. The research goal is finding appropriate operating parameters to achieve energy efficiency. Thus, an operation algorithm with two modes is proposed, i.e., one to search the best operating parameters and one for normal operation with the best parameters. The experimental evaluation showed 11.27% reduction in energy consumption, indicating a good applicability of the algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.10 no.5
• /
• pp.2310-2325
• /
• 2016

In this paper, we provide a trajectory-generation algorithm that can identify pedestrians in real time. Typically, the contours for the extraction of pedestrians from the foreground of images are not clear due to factors including brightness and shade; furthermore, pedestrians move in different directions and interact with each other. These issues mean that the identification of pedestrians and the generation of trajectories are somewhat difficult. We propose a new method for trajectory generation regarding multiple pedestrians. The first stage of the method distinguishes between those pedestrian-blob situations that need to be merged and those that require splitting, followed by the use of trained decision trees to separate the pedestrians. The second stage generates the trajectories of each pedestrian by using the point-correspondence method; however, we introduce a new point-correspondence algorithm for which the A* search method has been modified. By using fuzzy membership functions, a heuristic evaluation of the correspondence between the blobs was also conducted. The proposed method was implemented and tested with the PETS 2009 dataset to show an effective multiple-pedestrian-tracking capability in a pedestrian-interaction environment.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.33 no.1
• /
• pp.80-90
• /
• 2010

Performance management is very popular in business area and seems to be an exciting topic. Despite significant research efforts and myriads of performance metrics, performance management today as a rigorous approach is still in an immature state and metrics are often selected based on intuitive and heuristic approach. In a R&D sector, the difficulty to select the proper performance metrics is even more increasing due to the natural characteristics of R&D such as unique or domain-specific problems. In this paper, we present a way of presenting R&D performance framework using ontology language. Based on this, the specific metrics can be derived by reusing or inheriting the context in the framework. The proposed ontological framework is formalized using OWL(Ontology Web Language) and metrics selection rules satisfying the characteristics of R&D are represented in SWRL(Semantic Web Rule Language). Actual metrics selection procedure is carried out using JESS rule engine, a plug-in to Prot$\acute{e}$g$\acute{e}$, and illustrated with an example, incorporating a prevalent R&D performance model : TVP(Technology Value Pyramid).

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.37 no.1
• /
• pp.50-59
• /
• 2014

In this paper, we develop an efficient approach to solve a multiple-item budget-constraint newsboy problem with a reservation policy. A conventional approach for solving such problem utilizes an approximation for the evaluation of an inverse of a Gaussian cumulative density function when the argument of the function is small, and a heuristic method for finding an optimal Lagrangian multiplier. In contrast to the conventional approach, this paper proposes more accurate method of evaluating the function by using the normalization and an effective numerical integration method. We also propose an efficient way to find an optimal Lagrangian multiplier by proving that the equation for the budget-constraint is in fact a monotonically increasing function in the Lagrangian multiplier. Numerical examples are tested to show the performance of the proposed approach with emphases on the behaviors of the inverse of a Gaussian cumulative density function and the Lagrangian multiplier. By using sensitivity analysis of different budget constraints, we show that the reservation policy indeed provides greater expected profit than the classical model of not having the reservation policy.

• The Transactions of the Korean Institute of Electrical Engineers A
• /
• v.48 no.11
• /
• pp.1382-1387
• /
• 1999

This paper presents an optimal fuzzy power system stabilizer to damp out low frequency oscillation. So far fuzzy controllers have been applied to power system stabilizing controllers due to its excellent properties on the nonlinear systems. But the design process of fuzzy logic power system stabilizer requires empirical and heuristic knowledge of human experts as well as many trial-and-errors in general. This paper presents and optimal design method of the fuzzy logic stabilizer using the genetic algorithm. Non-symmetric membership functions are optimally tuned over an evaluation function. The present inputs of fuzzy stabilizer are torque angle error and the change of torque angle error without loss of generality. The coding method used in this paper is concatenated binary mapping. Each linguistic fuzzy variable, defined as the peak of a membership function, is assigned by the mapping from a minimum value to a maximum value using eight bits. The tournament selection and the elitism are used to keep the worthy individuals in the next generation. The proposed system is applied to the one-machine infinite-bus model of a power system, and the results showed a promising possibility.

• Journal of information and communication convergence engineering
• /
• v.9 no.4
• /
• pp.379-384
• /
• 2011

The scope of the problems that could be solved by monitoring and the improvement of the recognition time is directly correlated to the performance of the management function of the business process. However, the current monitoring process of business activities decides whether to apply warnings or not by assuming a fixed environment and showing expressions based on the design rules. Also, warnings are applied by carrying out the measuring process when the event attribute values are inserted at every point. Therefore, there is a limit for distinguishing the range of occurrence and the level of severity in regard to the new external problems occurring in a complicated environment. Such problems cannot be ed. Also, since it is difficult to expand the range of problems which can be possibly evaluated, it is impossible to evaluate any unexpected situation which could occur in the execution period. In this paper, a process-evaluating model based on the goal scenario is suggested to provide constant services through the current monitoring process in regard to the service demands of the new scenario which occurs outside. The new demands based on the outside situation are analyzed according to the goal scenario for the process activities. Also, by using the meta-heuristic algorithm, a similar process model is found and identified by combining similarity and interrelationship. The process can be stopped in advance or adjusted to the wanted direction.

• Smart Media Journal
• /
• v.7 no.3
• /
• pp.9-15
• /
• 2018

This paper proposes an optimal gain modification method of the Multichannel Wiener filter (MWF) using speech presence probabilities. Conventional gain modification methods of MWFs have the problem of the increase of speech distortions while reducing residual noises with its relative heuristic approach. However, the proposed optimal gain modification method, derived by solving the unconstrained minimization problem of the probability-involved cost function, reduces amounts of residual noises and signal distortions simultaneously. Through an evaluation of the filtered waveforms and spectrograms, it is verified that the proposed method results in an improved SNR with less signal distortions compared to the conventional MWF.

• Steel and Composite Structures
• /
• v.18 no.2
• /
• pp.289-303
• /
• 2015

This study presents a strategy so-called Subspace Search Mechanism (SSM) for reducing the computational time for convergence of population based metaheusristic algorithms. The selected metaheuristic for this study is the Cuckoo Search algorithm (CS) dealing with size optimization of trusses. The complexity of structural optimization problems can be partially due to the presence of high-dimensional design variables. SSM approach aims to reduce dimension of the problem. Design variables are categorized to predefined groups (subspaces). SSM focuses on the multiple use of the metaheuristic at hand for each subspace. Optimizer updates the design variables for each subspace independently. Updating rules require candidate designs evaluation. Each candidate design is the assemblage of responsible set of design variables that define the subspace of interest. SSM is incorporated to the Cuckoo Search algorithm for size optimizing of three small, moderate and large space trusses. Optimization results indicate that SSM enables the CS to work with less number of population (42%), as a result reducing the time of convergence, in exchange for some accuracy (1.5%). It is shown that the loss of accuracy can be lessened with increasing the order of complexity. This suggests its applicability to other algorithms and other complex finite element-based engineering design problems.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.47 no.8
• /
• pp.590-598
• /
• 2019

Today, satellites are widely used in many fields like communication and image recoding. The image acquired by satellites contains variety information of wide region. Therefore, they are used for agriculture, resource exploitation and management, and military purpose. The satellite is required to acquire images effectively in a given time period. Because the period that satellites can acquire images is very restrictive. In this study, the modeling of processing time and attitude maneuvering for satellite image acquisition is performed. From this modeling, mission planning algorithm using heuristic evaluation function is suggested and performance of the proposed algorithm is verified by numerical simulation.