• Proceedings of the Korea Inteligent Information System Society Conference
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• 2002.05a
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• pp.429-434
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• 2002

For companies assembling end products from sub assemblies or components, MRP (Material Requirement Planning) logic is frequently used to synchronize and pace the production activities for the required parts. However, in MRP, the planning of operational-level activities is left to short term scheduling. So, we need a good scheduling algorithm to generate feasible schedules taking into account shop floor characteristics and multi-level job structures used in MRP. In this paper, we present a GA (Genetic Algorithm) solution for this complex scheduling problem based on a new gene to reflect the machine assignment, operation sequences and the levels of the operations relative to final operation. The relative operation level is the control parameter that paces the completion timing of the components belonging to the same branch in the multi-level job hierarchy. In order to revise the fixed relative level which solutions are confined to, we apply large step transition in the first step and GA in the second step. We compare the genetic algorithm and 2-phase optimization with several dispatching rules in terms of tardiness for about forty modified standard job-shop problem instances.

• Industrial Engineering and Management Systems
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• v.15 no.1
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• pp.11-18
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• 2016

This paper considers a scheduling problem in a flexible job shop with a reconfigurable manufacturing cell. The flexible job shop has both operation and routing flexibilities, which can be represented in the form of a multiple process plan, i.e. each part can be processed through alternative operations, each of which can be processed on alternative machines. The scheduling problem has three decision variables: (a) selecting operation/machine pairs for each part; (b) sequencing of parts to be fed into the reconfigurable manufacturing cell; and (c) sequencing of the parts assigned to each machine. Due to the reconfigurable manufacturing cell's ability of adjusting the capacity, functionality and flexibility to the desired levels, the priority scheduling approach is proposed in which the three decisions are made at the same time by combining operation/machine selection rules, input sequencing rules and part sequencing rules. To show the performances of various rule combinations, simulation experiments were done on various instances generated randomly using the experiences of the manufacturing experts, and the results are reported for the objectives of minimizing makespan, mean flow time and mean tardiness, respectively.

• Industrial Engineering and Management Systems
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• v.4 no.1
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• pp.23-35
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• 2005

This paper aims to develop a practical finite capacity MRP (FCMRP) system based on the needs of an automotive parts manufacturing company in Thailand. The approach includes a linear goal programming model to determine the optimal start time of each operation to minimize the sum of penalty points incurred by exceeding the goals of total earliness, total tardiness, and average flow-time considering the finite capacity of all work centers and precedence of operations. Important factors of the proposed FCMRP system are penalty weights and dispatching rules. Effects of these factors on the performance measures are statistically analyzed based on a real situation of an auto-part factory. Statistical results show that the dispatching rules and penalty weights have significant effects on the performance measures. The proposed FCMRP system offers a good tradeoff between conflicting performance measures and results in the best weighted average performance measures when compared to conventional forward and forward-backward finite capacity scheduling systems.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2005.11a
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• pp.461-470
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• 2005

A dynamic supply chain that is composed of many different companies with different rent roles and interests allows free joining and secession. Buyers place orders simultaneously and manufacturers should compete each other for the orders. The purpose of our paper is how to find the optimal formation of supply chain ill a global viewpoint while allowing each member company to pursue his local goal The dynamic nature of supply chain formation causes the variation of cost depending on how many orders a manufacturer would accept. We propose a multi-agent based negotiation protocol that efficiently leads to the formation of optimal supply chain without giving up maximization of the individual profit in multi-agent environment of the make-to-order industry. The goal of the negotiation is to form a supply chain to minimize the overall sum of manufacturers' manufacturing cost, and earliness cost and tardiness cost based on SET model. We compare the negotiation protocol with Branch & Bound method. Finally, the validity and performance of buyer's negotiation has been tested experimentally.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.7
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• pp.1702-1710
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• 2009

In this paper, we propose a problem space based search(PSBS) algorithm to solve parallel machine scheduling problem considering rework probabilities. For each pair of a machine and a job type, rework probability of each job on a machine can be known through historical data acquisition. Neighborhoods are generated by perturbing four problem data vectors (processing times, due dates, setup times, and rework probabilities) and evaluated through the efficient dispatching heuristic (EDDR). The proposed algorithm is measured by maximum lateness and the number of reworked jobs. We show that the PSBS algorithm is considerably improved from the result obtained by EDDR.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.11
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• pp.4174-4181
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• 2010

This paper presents an adaptive scheduling algorithm for manufacturing processes with non-stationary rework probabilities. The adaptive scheduling scheme named by hybrid Q-learning algorithm is proposed in this paper making use of the non-stationary rework probability and coupling with artificial neural networks. The proposed algorithm is measured by mean tardiness and the extensive computational results show that the presented algorithm gives very efficient schedules superior to the existing dispatching algorithms.

• The KIPS Transactions:PartB
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• v.15B no.5
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• pp.413-420
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• 2008

Network bandwidth is one of the major factors that impact the cost of a video service. In this paper we propose approaches to reducing the bandwidth requirement for transporting MPEG-4 video traffic over wireless LANs while guaranteeing a required level of quality of service(QoS). To support high quality video playbacks, video frames must be transported to the client prior to their playback times. A real-time transmission scheduling is used for this purpose, which transmits each frame assigned with a priority according to its importance. It addresses the challenge for a scheduling algorithm that efficiently handles the changing workloads of MPEG-4 video traffic. The goal of our research is to maximize the number of frames that are transported within their deadlines while minimizing the tardiness of frames that missed their deadlines. The performance of the proposed method is compared with that of similar service mechanisms through extensive simulation experiments.

• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.1
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• pp.39-46
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• 2017

Today, mobile devices are becoming essential for everyday life, and integration of mobile computing, situation recognition and intellectual service accelerates mobile interaction. Surrounding intelligence detection technology is extremely important. These technologies can automatically acquire and recognize surrounding information and situations. Situation recognition can realize wide-range mobile recognition for intellectual services of users' diverse activities, by distinguishing many surrounding devices and recognizing their situations. Thus, this paper suggests application for students' mobile authentication such as college campus attendance authentication, and redesign existing plastic student ID as NFC-compatible mobile authentication system. Experiment results proved NFC-compatible mobile touch-based interactions can maximize the strengths of NFC technology because it can recognize limits in some situations such as tardiness and absences by automating student validation and preventing far-distance reading.

• Journal of the Korean Operations Research and Management Science Society
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• v.17 no.1
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• pp.41-41
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• 1992

In the real world situations that some jobs need be processed only on certain limited machines frequently occur due to the capacity restrictions of machines such as tools fixtures or material handling equipment. In this paper we consider n-job non-preemptive and m parallel machines scheduling problem having two machines group. The objective function is to minimize the sum of earliness and tardiness with different release times and due dates. The problem is formulated as a mixed integer programming problem. The problem is proved to be Np-complete. Thus a heuristic is developed to solve this problem. To illustrate its suitability and efficiency a proposed heuristic is compared with a genetic algorithm and tabu search for a large number of randomly generated test problems in ship engine assembly shop. Through the experimental results it is showed that the proposed algorithm yields good solutions efficiently.

• Journal of Intelligence and Information Systems
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• v.12 no.2
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• pp.99-123
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• 2006

In an effect to composite an optimal supply chain, this study has introduced an agent-based negotiation as a method to assign a lot of orders to a large number of participants. As a resources allocation mechanism to form a strategic cooperation based on information sharing between supply chain members(buyers, manufacturers, suppliers), this agent negotiation provides coordination functions allowing all participants to make a profit and accomplishing Pareto optimum solution from the viewpoint of a whole supply chain. A SET model-based scheduling takes into consideration both earliness production cost and tardiness production cost, along with a competitive relationship between multiple participants. This study has tried to prove that the result of an agent-based negotiation is a Pareto optimal solution under the dynamic supply chain environment, establishing the mathematical formulation for a performance test, and making a comparison with the heuristic Branch & Bound method.