• Proceedings of the IEEK Conference
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• 2002.07a
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• pp.265-268
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• 2002

Parallel-computation is very interesting topic. This paper describes that we apply it into the Boltzmann machine with the Parallel-Transit-Evaluation Method successfully.

• Management Science and Financial Engineering
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• v.11 no.2
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• pp.19-43
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• 2005

This paper considers a variation of the customer order scheduling problem, and the variation is the case where the machine-job assignment is fixed. We examine the parallel machine environment, and the objective is to minimize the sum of the completion times of the batches. While a machine can process only one job at a time, different machines can simultaneously process different jobs in a batch. The recognition version of this problem is known to be NP-complete in the strong sense even if there exist only two parallel machines. When there are an arbitrary number of parallel machines, we establish three lower bounds and develop a dynamic programming (DP) algorithm which runs in exponential time on the number of batches. We present two simple but intuitive heuristics, SB and GR, and find some special cases where SB and GR generate an optimal schedule. We also find worst case upper bounds on the relative error. For the case of the two parallel machines, we show that GR generates an optimal schedule when processing times of all batches are equal. Finally, the heuristics and the lower bounds are empirically evaluated.

• Korean Management Science Review
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• v.12 no.3
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• pp.177-185
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• 1995

This paper presents a Tabu Search method to minimize a number of tardy jobs in the nonidentical parallel machine scheduling. The Tabu Search method employs a restricted neighborhood for the reduction of computation time. In this paper, we use two different types of method for a single machine scheduling. One is Moore's algorithm and the other is insertion method. We discuss computational experiments on more than 1000 test problems.

• Management Science and Financial Engineering
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• v.13 no.2
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• pp.47-77
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• 2007

This paper considers a scheduling problem where a customer orders multiple products(jobs) from a production facility. The objective is to minimize the sum of the order(batch) completion times. While a machine can process only one job at a time, multiple machines can simultaneously process jobs in a batch. Although each job has a unique processing time, we consider the case where batch processing times are identical. This simplification allows us to develop heuristics with improved performance bounds. This problem was motivated by a real world problem encountered by foreign electronics manufacturers. We first establish the complexity of the problem. For the two parallel machine case, we introduce two simple but intuitive heuristics, and find their worst case relative error bounds. One bound is tight and the other bound goes to 1 as the number of orders goes to infinity. However, neither heuristic is superior for all instances. We extend one of the heuristics to an arbitrary number of parallel machines. For a fixed number of parallel machines, we find a worst case bound which goes to 1 as the number of orders goes to infinity. Then, a tighter bound is found for the three parallel machine case. Finally, the heuristics are empirically evaluated.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.6
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• pp.161-169
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• 2011

Recent intelligent video surveillance system asks for development of more advanced technology for analysis and recognition of video data. Especially, machine learning algorithm such as Support Vector Machine (SVM) is used in order to recognize objects in video. Because SVM training demands massive amount of computation, parallel processing technique is necessary to reduce the execution time effectively. In this paper, we propose a parallel processing method of SVM training with a multi-core processor. The results of parallel SVM on a 4-core processor show that our proposed method can reduce the execution time of the sequential training by a factor of 2.5.

• The Journal of Natural Sciences
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• v.5 no.2
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• pp.39-43
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• 1992

Detection of parallelism by a compiler is very desirable from a user's point of view. However, even the most sophisticated techniques to detect parallelism trip on trivial impediments, such as conditionals, function calls, and input/output statements, fail to detect most of the parallelism present in a program. Some parallelizing compilers provide feedback to the user when they have difficulty in deciding about parallel execution. Under these circumstances, a programmer has to restructure the source code to aid the detection of parallelism. But, functional and declarative languages can be said to offer many advantages in this context. Functional programs are easier to reason about because their output is determinate, that is, independent of the order of evaluation. However, functional languages traditionally have lacked good facilities for manipulating arrays and matrices. In this paper, a declarative language called Id has been proposed as a solution to some of these problems.

• Proceedings of the KSME Conference
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• 2000.11a
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• pp.535-540
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• 2000

This paper presents the development of a Parallel-Typed CNC Machining Tool. It is specially designed to machine a complex shaped workpiece by controlling the orientation of the tool. The inverse/direct kinematics of a parallel mechanism is derived and implemented in a PC based controller. With graphics icons, the GUI (Graphic User Interface) program is developed for the CNC programing. The calibration is accomplished by geometric constraint motion, which is a parallel motion of the platform with respect to a table. The calibration result is introduced and the future study is proposed.

• Korean Management Science Review
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• v.29 no.3
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• pp.157-168
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• 2012

In this study, we consider an order promising problem at parallel machine shops where orders arrive dynamically. We develop methods for the problem, which instantly quote the due-dates of arrived orders. In this study, we first propose methods which can estimate flow times of orders, in which the current and future inventory status as well as the specific scheduling scheme used in the shop are taken into account, and then the due-dates are set by the order promising methods using the estimation results. The quoted due-dates of orders are compared with the actual completion times of those which are obtained from the simulation runs. The series of computational experiments show that the superior performance of the proposed methods in terms of the accuracy of due-date quotation.

• Journal of the Korean Operations Research and Management Science Society
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• v.39 no.3
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• pp.83-91
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• 2014

We consider the problem of scheduling identical jobs with sequence-independent setup times on parallel machines. The objective is to minimize total completion times. We present the pseudopolynomial-time algorithm for the case with a fixed number of machines and an efficient approximation algorithm for our problem with identical setup times, which is known to be NP-hard even for the two-machine case.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.1
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• pp.65-73
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• 2015

This paper considers a parallel-machine scheduling problem with dedicated and common processing machines using GA (Genetic Algorithm). Non-identical setup times, processing times and order lot size are assumed for each machine. The GA is proposed to minimize the total-tardiness objective measure. In this paper, heuristic algorithms including EDD (Earliest Due-Date), SPT (Shortest Processing Time) and LPT (Longest Processing Time) are compared with GA. The effectiveness and suitability of the GA are derived and tested through computational experiments.