• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.05a
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• pp.615-619
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• 2004

This paper considers a variation of customer order scheduling problems. The variation is the case where machine-job assignment is fixed, and the objective is to minimize the sum of the completion times of the batches. In customer order scheduling problems, jobs are dispatched in batches. While a machine can process only one job at a time, multiple machines can simultaneously process jobs in a batch. We first establish a couple of lower bounds. Then, we develop a dynamic programming (DP) algorithm that runs in exponential time on the number of batches when there exist two machines. For the same problem with arbitrary number of machines, we present two simple heuristics, which use simple scheduling rules such as shortest batch first and shortest makespan batch first rules. Finally, we empirically evaluate the heuristics.

• Journal of the Korean Operations Research and Management Science Society
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• v.21 no.1
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• pp.115-129
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• 1996

A reliability Acceptance Sampling Plan (RASP) is developed for testing the exponential mean lifetime under the periodic (i. e., equally-spaced) inspection and Type I censoring. Under the periodic inspection, the exact sampling distribution of maximum likelihood (ML) estimator of mean can not be derived. Hence sample size and acceptance criterion are determined by the algorithm proposed on the basis of Monte Carlo simulation such that the producer's and consumer's risks are satisfied for given censoring time and number of inspections. In addition, the developed RASP is compared in terms of sampling size, OC curve, and expected completion time. The effects for the RASP by the chosen inspection scheme are also discussed.

• Journal of applied mathematics & informatics
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• v.18 no.1_2
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• pp.383-391
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• 2005

The paper is devoted to some flow shop scheduling problems, where job processing times are defined by functions dependent on their positions in the schedule. An example is constructed to show that the classical Johnson's rule is not the optimal solution for two different models of the two-machine flow shop scheduling to minimize makespan. In order to solve the makespan minimization problem in the two-machine flow shop scheduling, we suggest Johnson's rule as a heuristic algorithm, for which the worst-case bound is calculated. We find polynomial time solutions to some special cases of the considered problems for the following optimization criteria: the weighted sum of completion times and maximum lateness. Some furthermore extensions of the problems are also shown.

• Proceedings of the KIEE Conference
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• 1988.07a
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• pp.941-944
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• 1988

To assure a successful completion of an assigned task without interruption, the hand of mechnical manipulator often travels along a preplanned path. This paper presents a method of obtaining a time sechdule of velocities and acceleration along the path, under the constraints. Because of the involvement of a linear performance index and a largr number of nonlinear constraints, the "method of approximate programming (AMP)" is applied. To overcome the false solutions AMP is modified. To reduce the computing time, a "direct approximate programming algorithm (DAPA)" is developed.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.37 no.4
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• pp.187-192
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• 2014

Lot-streaming is the process of splitting a job (lot) into sublots to allow the overlapping of operations between successive machines in a multi-stage production system. A new genetic algorithm (NGA) is proposed for an n-job, m-machine, lot-streaming flow shop scheduling problem with equal-size sublots in which the objective is to minimize the total stretch. The stretch of a job is the ratio of the amount of time the job spent before its completion to its processing time. NGA replaces the selection and mating operators of genetic algorithms (GAs) by marriage and pregnancy operators and incorporates the idea of inter-chromosomal dominance and individuals' similarities. Extensive computational experiments for medium to large-scale lot-streaming flow-shop scheduling problems have been conducted to compare the performance of NGA with that of GA.

• Journal of Communications and Networks
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• v.14 no.2
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• pp.140-150
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• 2012

In this paper, we investigate the optimal packet scheduling problem in a two-user multiple access communication system, where the transmitters are able to harvest energy from the nature. Under a deterministic system setting, we assume that the energy harvesting times and harvested energy amounts are known before the transmission starts. For the packet arrivals, we assume that packets have already arrived and are ready to be transmitted at the transmitter before the transmission starts. Our goal is to minimize the time by which all packets from both users are delivered to the destination through controlling the transmission powers and transmission rates of both users. We first develop a generalized iterative backward waterfilling algorithm to characterize the maximum departure region of the transmitters for any given deadline T. Then, based on the sequence of maximum departure regions at energy arrival instants, we decompose the transmission completion time minimization problem into convex optimization problems and solve the overall problem efficiently.

• IE interfaces
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• v.11 no.2
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• pp.159-176
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• 1998

In the motor manufacturing system with the properties of short delivery and order based production, the process plan is performed individually for each order by the expert of process plan after the completion of the detail design process to satisfy the specification to be required by customer. Also it is hard to establish the standard process plan in reality because part routings and operation times are varied for each order. Hence, the production planner has the problem that is hard to establish the production schedule releasing the job to the factory because there occurs the big difference between the real time to be completed the process plan and the time to be required by the production planner. In this paper, we study the decision supporting system for the process plan based on knowledge base concept. First, we represent the knowledge of process planner as a database model through the modified POI-Feature graph. Then we design and implement the decision supporting system imbedded in the heuristic algorithm in the client/server environment using the ORACLE relational database management system.

• International journal of advanced smart convergence
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• v.9 no.4
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• pp.62-73
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• 2020

In this paper, we present electronic acupuncture needles we have developed using intelligence technology based on Bluetooth in order to allow anyone to simply receive customized remote diagnosis and treatment by clicking on the menu of the smartphone regardless of time and place. In order to determine the health condition and disease of patients, we have developed a software and a hardware of electronic acupuncture needles, operating on Bluetooth which transmits biometric data to oriental medical doctors using the functions of automatically determining pulse diagnosis, tongue diagnosis, and oxygen saturation; the functions are most commonly used in herbal treatment. In addition, using fuzzy logic and reasoning based on smartphones, we present in this paper an algorithm and the results of completion of hardware implementation for electronic acupuncture needles, appropriate for the body conditions of patients; the algorithm and the hardware implementation are for a treatment time duration by electronic acupuncture needles, an automatic determinations of pulse diagnosis, tongue diagnosis, and oxygen saturation, a function implementation for automatic display of acupuncture point, and a strength adjustment of electronic acupuncture needles. As a result of our simulation, we have shown that the treatment of patients, performed using an Electronic Acupuncture Needles based on intelligence, is more efficient compared to the treatment that was performed before.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2016.05a
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• pp.166-167
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• 2016

Unlike the past, supported by the development of digital technologies, free-form buildings are frequently designed with creative thoughts of architectural designers. However, there are some difficulties preventing successfully completion of projects, like reduced productivity and increased construction duration and cost upon the process of producing and installing concrete panels for free-form structures. In particular, there are active studies on the CNC machine for production of free-form concrete panels. Yet, it is difficult to effectively and easily come up with information on production and installation of free-form, curve-surfaced panels which are difficult to be mathematically defined. This requires a lot of manpower and time to implement the curved surfaces of free-form buildings as intended by architects. Accordingly, it needs a model that can effectively create production-installation data of free-form concrete panels for successful free-form building projects. Thus, the purpose of the study is to suggest data estimation model of production-installation using mathematical algorithm in free-form concrete panels. The study results will realize effective production and installation of free-form concrete members, allowing improved productivity of projects, reduced cost and shortened construction duration.

• Journal of the Korea Safety Management & Science
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• v.22 no.4
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• pp.65-74
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• 2020

Many of companies have made significant improvements for globalization and competitive business environment The supply chain management has received many attentions in the area of that business environment. The purpose of this study is to generate realistic production and distribution planning in the supply chain network. The planning model determines the best schedule using operation sequences and routing to deliver. To solve the problem a hybrid approach involving a genetic algorithm (GA) and computer simulation is proposed. This proposed approach is for: (1) selecting the best machine for each operation, (2) deciding the sequence of operation to product and route to deliver, and (3) minimizing the completion time for each order. This study developed mathematical model for production, distribution, production-distribution and proposed GA-Simulation solution procedure. The results of computational experiments for a simple example of the supply chain network are given and discussed to validate the proposed approach. It has been shown that the hybrid approach is powerful for complex production and distribution planning in the manufacturing supply chain network. The proposed approach can be used to generate realistic production and distribution planning considering stochastic natures in the actual supply chain and support decision making for companies.