• 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.

• Journal of the Korean Society for Precision Engineering
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• v.26 no.10
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• pp.12-17
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• 2009

• 한국정보통신설비학회:학술대회논문집
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• 2007.08a
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• pp.371-375
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• 2007

In this paper, we have implemented the device management system to upgrade T-PAK software in mobile phone. The hybrid scheduling method and selective upgrade method are proposed. Hybrid scheduling method is based on distribution of delivery data in accordance with network traffic load and service priority from device management server to mobile phone. Selective upgrade method manages DSL classified by T-PAK software version to be upgrade using version management established in OMA DM SCOMO. Key mechanism of selective upgrade method is to only deliver DSL to be replaced to the mobile phone. We made an experiment on two methods using MS-700T terminals. The experimental result shows that the proposed method is faster than normal from delivery time standpoint.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.11A
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• pp.1106-1112
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• 2007

As a demand for high speed uplink packet services increases, the WCDMA enhanced uplink, also known as high speed uplink packet access (HSUPA), has been specified in release 6 by 3GPP. This HSUPA will provide various types of multimedia services, such as real-time video streaming, gaming, VoIP, and FTP. Generally, the performance of HSUPA is dominated by scheduling policy. Therefore, it is required to design a scheduling algorithm considering the traffic characteristics to provide QoS guaranteed services in various traffic environments. In this paper, we propose a scheduling algorithm considering the traffic characteristics to guarantee QoS in a mixed traffic environment. Finally, the performance of the proposed scheduling algorithm is evaluated in terms of average packet delay, packet delay jitter, and system throughput using a system level simulator.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.2
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• pp.111-120
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• 2017

This paper proposes an improved standard genetic algorithm (GA) of making a near optimal schedule for integrated process planning and scheduling problem (IPPS) considering tool flexibility and tool related constraints. Process planning involves the selection of operations and the allocation of resources. Scheduling, meanwhile, determines the sequence order in which operations are executed on each machine. Due to the high degree of complexity, traditionally, a sequential approach has been preferred, which determines process planning firstly and then performs scheduling independently based on the results. The two sub-problems, however, are complicatedly interrelated to each other, so the IPPS tend to solve the two problems simultaneously. Although many studies for IPPS have been conducted in the past, tool flexibility and capacity constraints are rarely considered. Various meta-heuristics, especially GA, have been applied for IPPS, but the performance is yet satisfactory. To improve solution quality against computation time in GA, we adopted three methods. First, we used a random circular queue during generation of an initial population. It can provide sufficient diversity of individuals at the beginning of GA. Second, we adopted an inferior selection to choose the parents for the crossover and mutation operations. It helps to maintain exploitation capability throughout the evolution process. Third, we employed a modification of the hybrid scheduling algorithm to decode the chromosome of the individual into a schedule, which can generate an active and non-delay schedule. The experimental results show that our proposed algorithm is superior to the current best evolutionary algorithms at most benchmark problems.

• Korean Journal of Construction Engineering and Management
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• v.5 no.5 s.21
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• pp.135-142
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• 2004

This paper proposes the CPM bar chart (CBC), a hybrid of the bar chart and the critical pad method (CPM). The CBC overcomes shortages of the fenced bar chart, while still keeping advantages. The fence with direction is applied instead of the broken fence, which triggers considerable problems to identify and apply in the fenced bar chart. In addition, the notorious task to find dummy activities is no longer required. Upon the benefits of simplicity in the bar chart and logical work sequence in the CPM network. the CBC provides a relatively easy way to create and understand a schedule, thus improving communication quality between project participants. With the advantages, the CBC can also be effectively applied to various scheduling techniques such as resource constrained scheduling, resource leveling, scheduling with activity split, delay impact analysis, etc.

• The Transactions of the Korea Information Processing Society
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• v.6 no.4
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• pp.959-968
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• 1999

several papers have reported that parallel heuristics or hybrid approaches combining several heuristics can get better results. However, the parallelization and hybridization of any search methods on the single CPU type computer need enormous computation time. that case, we need more elegant combination method. For this purpose, we propose Fast Model of Parallel Heuristics(FMPH). FMPH is based on the island model of parallel genetic algorithms and takes local search to the elite solution obtained form each island(sub group). In this paper we introduce how can we adapt FMPH to the job-shop scheduling problem notorious as the most difficult NP-hard problem and report the excellent results of several famous benchmark problems.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.33 no.4
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• pp.58-68
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• 2010

Particle Swarm Optimization (PSO) which has been well known to solve continuous problems can be applied to discrete combinatorial problems. Several DPSO (Discrete Particle Swarm Optimization) algorithms have been proposed to solve discrete problems such as traveling salesman, vehicle routing, and flow shop scheduling problems. They are different in representation of position and velocity vectors, operation mechanisms for updating vectors. In this paper, the performance of 5 DPSOs is analyzed by applying to traditional Traveling Salesman Problems. The experiment shows that DPSOs are comparable or superior to a genetic algorithm (GA). Also, hybrid PSO combined with local optimization (i.e., 2-OPT) provides much improved solutions. Since DPSO requires more computation time compared with GA, however, the performance of hybrid DPSO is not better than hybrid GA.

• International Journal of Precision Engineering and Manufacturing
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• v.1 no.2
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• pp.124-131
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• 2000

A shop floor can be considered as and importand level to develop a Computer Integrated Manufacturing system (CIMs). The shop foor is a dynamic environment where unexpected events contrinuously occur, and impose changes to planned activities. The shop floor should adopt an appropriate control system that is responsible for scheduling coordination and moving the manufacturing material and information flow. In this paper, the architecture of the hybrid control model identifies three levels; i.e., the shop floor controller (SFC), the cell controller(CC) and the equipment controller (EC). The methodology for developing these controller is employ an object-oriented approach for static models and IDEF0 for function models for dispatching a job. SFC and CC are coordinated by employing a multi-factors bidding and an adapted Analytic Hierarchy Process(AHP) prove applicability of the suggested method. Test experiment has been conducted by with the shopfloor, consisting of six manufacturing cells.

• Journal of Korea Multimedia Society
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• v.10 no.7
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• pp.882-892
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• 2007

In this paper, we propose a mechanism for both scheduling the hybrid-task set which consists of periodic and aperiodic tasks and recovering tasks with transient faults on the level of the operating system. Existing embedded operating systems would not provide the scheduling of both periodic and aperiodic tasks. Also because of not supporting the recovery of task failures, they can not prevent system failure from transient task faults. Proposed method, on the level of operating system, is able to not only meet the deadlines of all periodic tasks but also complete the execution of aperiodic tasks. In addition, it is able to prevent the system failure from transient task faults by recovering the task faults.