• Journal of Korean Society of Industrial and Systems Engineering
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• v.8 no.11
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• pp.45-56
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• 1985

This thesis studies the order release scheduling by lead time offsetting technique in MRP system. MRP is the process of working backward from the scheduled completion dates of end products or major assemblies to determine the dates and quantities when the various component parts and materials are to be ordered. It aims getting the right quantity of component parts to the right places at the right time with a schedule that puts each parts or subassembly into stock shortly ahead of the need for that parts or subassembly. The planned order release point of a item can be easily decided when the scheduled completion date and planned lead time is certain and known before by lead time offsetting technique in MRP system.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.36 no.1
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• pp.86-95
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• 2013

The distribution cost increases constantly because of the growth of yield, globalization of accounts and the generalization of e-commerce. This paper is concerned with scheduling on the allocation of workers to maximize the amount of order process in warehouse logistics system. The problem is to determine the number of operators in each process by the sequential time zone. We considered that the number of operators is restricted to the current level and also the process time is changed by putting some resources into the process. In each stage, we suggest some considerations for the allocation of workers and estimate the maximum amount of order process of the alternatives. We analyzed the alternatives using simulation s/w Arena with real cases.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.6
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• pp.115-121
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• 2015

In this paper, we proposed an iterative data-flow optimal scheduling algorithm based on genetic algorithm for high-performance multiprocessor. The basic hardware model can be extended to include detailed features of the multiprocessor architecture. This is illustrated by implementing a hardware model that requires routing the data transfers over a communication network with a limited capacity. The scheduling method consists of three layers. In the top layer a genetic algorithm takes care of the optimization. It generates different permutations of operations, that are passed on to the middle layer. The global scheduling makes the main scheduling decisions based on a permutation of operations. Details of the hardware model are not considered in this layer. This is done in the bottom layer by the black-box scheduling. It completes the scheduling of an operation and ensures that the detailed hardware model is obeyed. Both scheduling method can insert cycles in the schedule to ensure that a valid schedule is always found quickly. In order to test the performance of the scheduling method, the results of benchmark of the five filters show that the scheduling method is able to find good quality schedules in reasonable time.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.885-888
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• 1995

Virtual Manufacturing System(VMS) is a computer model that represents the precise and whole structure of manufacturing system and simulates their physical and logical behavior in operation. In this paper, a real time simulation for the virtual factory is proposed to integrate a process planning with scheduling under distributed environments. In order to communicate the information under distributed environment, weuse a sever/client concept and socket program. the VMS is implemented on the internet environment.

• Journal of the military operations research society of Korea
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• v.9 no.1
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• pp.51-61
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• 1983

Lagrangian relaxation is used to the problem of scheduling jobs on unrelated parallel processors with the objective of minimizing makespan. The implicit condition for optimality is drawn out explicitly in order to apply the subgradient algorithm. To obtain the optimal solution, branch-and-bound-search method is devised. In the search, the special structure of the problem is exploited effectively, Some computational experiences with the algorithm are presented, and comparisons are made with the Land and Doig method.

• Journal of the Korean Operations Research and Management Science Society
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• v.4 no.1
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• pp.69-77
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• 1979

A single machine stochastic scheduling problem is considered. Associated with each job is its random processing time and random deferral cost. The criterion is to order the jobs so as to minimize the sum of the deferral costs. The expected sum of the deferral costs is theroretically derived under the stochastic situation for each of several scheduling decision rules which are well known for the deterministic environment. It is also shown that certain stochastic problems can be reduced to equivalent deterministic problems. Two examples are illustrated to show the expected total deferral costs.

• Proceedings of the Safety Management and Science Conference
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• 2003.05a
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• pp.285-290
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• 2003

There is only one server available and arriving work require services from this server. Job are processed by the machine one at a time. The most common objective is to sequence jobs on the severs so as to minimize the penalty for being late, commonly called tardiness penalty Based on other objectives, many criteria may serve as s basis for developing job schedules. Therefore, this study tries to proposed that Scheduling by customer needs group for minimizing the problem and reducing inventory, product development time, cycle time, and order lead time.

• Journal of Korean Institute of Industrial Engineers
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• v.33 no.3
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• pp.290-302
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• 2007

This paper introduces several decision-making problems that need to be solved in order to facilitate the efficient operation of container terminals. These decision-making problems include the berth planning problem, the quay crane scheduling problem, the unload/load sequencing problem, the yard allocation problem, and the short-term scheduling of transporters and yard cranes. These problems can be classified into strategic decision problems, tactical decision problems, and real time operational decision problems. This paper proposes definitions of the problems that can be used to develop mathematical models for the problems.

• The KIPS Transactions:PartA
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• v.8A no.1
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• pp.16-26
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• 2001

This paper proposes an extended scheduler model that is an extension of the existing model proposed already in [4, 5], which consists of upper layer task scheduler and lower layer scheduling framework. However, in order to support aperiodic task scheduling, the task scheduler has been divided into two parts, such as periodic task control component and aperiodic task control component. Thus, the proposed model can support various bandwidth-preserving servers that can service aperiodic tasks. The model distinctly separates a classic monolithic kernel scheduler into several kernel components according to their functionality. This enables system developers to implement a new scheduling algorithm or aperiodic task server independent of complex low kernel mechanism, and reconfigure the system at need. In Real-Time Linux [6], we implemented the proposed scheduling framework representative scheduling algorithms, and server bandwidth-preserving servers on purpose to test. Throughout these implementations, we confirmed that a new algorithm or server could be developed independently without updates of complex low kernel modules. In order to verify efficiency of the proposed model, we measured the performance of several aperiodic task servers. The results showed this the performance of model, which even consisted of two hierarchical components and several modules, didnt have such high run-time overhead, and could efficiently support reconfiguration and scheduler development.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.1
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• pp.95-103
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• 2008

This paper deals with the problem of autolanding for aircraft under windshear environment for which the landing trajectory is given. It is well known that the landing maneuver in windshear turbulence is very dangerous and hard for the pilot to control because windshear is unpredictable in when and where it happens and its aerodynamic characteristics are complicated. In order to accomplish satisfactory autolanding maneuver in this environment, we propose a gain-scheduled controller. The proposed controller consists of three parts: PID controller, called baseline controller, which is designed to satisfy requirements of stability and performance without considering windshear, gain scheduler based on fuzzy logic, and safety decision logic, which decides if the current autolanding maneuver needs to be aborted or not. The controller is applied to a 6-DOF simulation model of the associated airplane in order to illustrate the effectiveness of the proposed control algorithm. It is noted that a cross wind in the lateral direction is included to the simulation model. From the simulation results it is observed that the proposed gain scheduled controller shows superior performance than the case of controller without gain scheduling even in severe downburst and tailwind region of windshear. In addition, touchdown along centerline of the runway is more precise for the proposed controller than for the controller without gain scheduling in the cross wind and the tailwind.