• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.11a
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• pp.473-474
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• 2010

• Journal of the Korea Society of Computer and Information
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• v.25 no.1
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• pp.21-27
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• 2020

In this paper, a hybrid scheduling algorithm is proposed for CMS(Combat Management System) to improve QoS(Quality of Service) based on DWDRR(Dynamic Weighted Deficit Round Robin) and priority-based scheduling method. The main proposed scheme, DWDRR is method of packet transmission through giving weight by traffic of queue and priority. To demonstrate an usefulness of proposed algorithm through simulation, efficiency in special section of the proposed algorithm is proved. Therefore, We propose hybrid algorithm between existing algorithm and proposed algorithm. Also, to prevent frequent scheme conversion, a hysteresis method is applied. The proposed algorithm shows lower packet loss rate and delay in the same traffic than existing algorithm.

• ETRI Journal
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• v.24 no.2
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• pp.172-175
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• 2002

This paper considers a packet-scheduling algorithm for a given combined traffic of unicast and multicast data packets and proposes a hybrid router with several dedicated buses for multicast traffic. Our objective is to develop a scheduling algorithm that minimizes schedule length for the given traffic in the hybrid router. We derive a lower bound and develop an optimal solution algorithm for the hybrid router.

• Journal of Intelligence and Information Systems
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• v.13 no.3
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• pp.63-82
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• 2007

In this paper, we propose an adaptive hybrid genetic algorithm (ahGA) approach for effectively solving multistage-based scheduling problems in flexible manufacturing system (FMS) environment. The proposed ahGA uses a neighborhood search technique for local search and an adaptive scheme for regulation of GA parameters in order to improve the solution of FMS scheduling problem and to enhance the performance of genetic search process, respectively. In numerical experiment, we present two types of multistage-based scheduling problems to compare the performances of the proposed ahGA with conventional competing algorithms. Experimental results show that the proposed ahGA outperforms the conventional algorithms.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.195-204
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• 2003

Network optimization is being increasingly important and fundamental issue in the fields such as engineering, computer science, operations research, transportation, telecommunication, decision support systems, manufacturing, and airline scheduling. Networks provide a useful way to modeling real world problems and are extensively used in practice. Many real world applications impose on more complex issues, such as, complex structure, complex constraints, and multiple objects to be handled simultaneously and make the problem intractable to the traditional approaches. Recent advances in evolutionary computation have made it possible to solve such practical network optimization problems. The invited talk introduces a thorough treatment of evolutionary approaches, i.e., hybrid genetic algorithms approach to network optimization problems, such as, fixed charge transportation problem, minimum cost and maximum flow problem, minimum spanning tree problem, multiple project scheduling problems, scheduling problem in FMS.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.187-190
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• 2003

Many manufacturing companies consider the integrated and concurrent scheduling because they need the global optimization technology that could manufacture various products more responsive to customer needs. In this paper, we propose an advanced scheduling model to generate the schedules considering resource constraints and precedence constraints in make-to-order (MTO) manufacturing environments. Precedence of work- in-process(WIP) and resources constraints have recently emerged as one of the main constraints in advanced scheduling problems. The advanced scheduling problems is formulated as a multiobjective mathematical model for generating operation schedules which are obeyed resources constraints, alternative workstations of operations and the precedence constraints of WIP in MTO manufacturing. For effectively solving the advanced scheduling problem, the multi-objective hybrid genetic algorithm (m-hGA) is proposed in this paper. The m-hGA is to minimize the makespan, total flow time of order, and maximum tardiness for each order, simultaneously. The m-hGA approach with local search-based mutation through swap mutation is developed to solve the advanced scheduling problem. Numerical example is tested and presented for advanced scheduling problems with various orders to describe the performance of the proposed m-hGA.

• Journal of Korean Institute of Industrial Engineers
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• v.21 no.3
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• pp.357-369
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• 1995

Wafer fabrication process is the most important and critical process in semiconductor manufacturing. The process is very complicated and hard to establish an efficient schedule due to its complexity. Furthermore, several performance indices such as due dates, throughput, cycle time and workstation utilizations are to be considered simultaneously for an efficient schedule, and some of these indices have negative correlations in performances each other. We develop an efficient heuristic scheduling algorithm; Hybrid Input Control Policy and Hybrid Dispatching Rule. Through numerical experiments, it is shown that the proposed Hybrid Scheduling Algorithm gives better performance compared with existing algorithms.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.05a
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• pp.947-951
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• 2005

The concept of group technology has been successfully applied to many production systems including flexible manufacturing systems. In this paper we apply group technology principles to the economic lot scheduling problem which has been intensively studied over 40 years. We obtain a production schedule of several family products on a single facility where setup times and costs can be reduced by using the concept of group technology. We develop a heuristic algorithm and a hybrid genetic algorithm for the group technology economic lot scheduling problem (GT-ELSP). Numerical example shows that the developed heuristic and the hybrid genetic algorithm outperform the existing heuristics.

• Journal of Korean Institute of Industrial Engineers
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• v.33 no.2
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• pp.213-220
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• 2007

This paper considers a two-stage hybrid flow shop scheduling problem for the objective of minimizing the number of tardy jobs. Each job is processed through the two production stages in stages, each of which has multiple identical parallel machines. The problem is to determine the allocation and sequence of jobs at each stage. A branch and bound algorithm that gives the optimal solutions is suggested that incorporates the methods to obtain the lower and upper bounds. Dominance properties are also suggested to reduce the search space. To show the performance of the algorithm, computational experiments are done on randomly generated problems, and the results are reported.

• ETRI Journal
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• v.26 no.3
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• pp.265-268
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• 2004

We develop a simple exact solution method for return link capacity allocation scheduling in a satellite interactive network using a hybrid code-division multiple access / time-division multiple access (CDMA/TDMA) scheme.