• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.2
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• pp.218-224
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• 2014

The logic-based scheduling language RCPSV may be used to model resource-constrained project scheduling problems with variants for minimizing the project completion time. A diagram-based, nonredundant enumeration algorithm for the RCPSV-problem is proposed and the correctness of the algorithm is proved.

• Proceedings of the IEEK Conference
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• 2000.11b
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• pp.188-191
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• 2000

This paper presents a register scheduling and allocation algorithm for high level synthesis. The proposed algorithm executes the low power scheduling to reduce the switching activity using shut down technique which was not unnecessary the calculation through the extraction DFG from VHDL description. Also, the register allocation algorithm determines the minimum register after the life time analysis of all variable. It is minimum the switching activity using graph coloring technique for low power consumption. The proposed algorithm proves the effect through various filter benchmark to adopt a new scheduling and allocation algorithm considering the low power.

• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.249-251
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• 2007

The proposed LDS(Link-status Dependent Scheduling) algorithm in HR-WPAN up to now aims at doing only throughput elevation of the whole network, when the crucial DEV(Device) is connected with worst-link relatively, throughput of this DEV becomes aggravation, The proposed the WGS(Worst-case Guaranteed Scheduling) _algorithm in this paper guarantees throughput of the DEV which is connected with worst-link in a certain degree as maintaining throughput of all DEVs identically even if a link-status changes, decreases delay of the whole network more than current LDS algorithm Therefore proposed WGS algorithm in this paper will be useful in case of guaranteeing throughput of a DEV which is connected worst-link in a certain degree in a design of HR-WPAN hereafter.

• Journal of the military operations research society of Korea
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• v.24 no.2
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• pp.162-169
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• 1998

This study presents an single machine scheduling algorithm minimize lateness of product by controlling machining speed. Generally, production scheduling uses the information of process planning. But the production scheduling algorithm has not considered the control of machining speed in its procedures. Therefore, the purpose of this study is to consider the machining speed in production scheduling algorithm for efficient production scheduling. Machining time and machining cost required to manufacture a piece of a product are expressed as a unimodal convex function with respect to machining speed, so it has minimal point at minimum time speed or the minimum cost speed. Therefore, because of considering the machining cost, the control of machining speed for the algorithm is executed between minimum speed and maximum speed. An example is demonstrated to explain the algorithm.

• Journal of Information Processing Systems
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• v.19 no.4
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• pp.450-464
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• 2023

To address the problems of large system overhead and low timeliness when dealing with task scheduling in mobile edge cloud computing, a task scheduling and resource management strategy for edge cloud computing based on an improved genetic algorithm was proposed. First, a user task scheduling system model based on edge cloud computing was constructed using the Shannon theorem, including calculation, communication, and network models. In addition, a multi-objective optimization model, including delay and energy consumption, was constructed to minimize the sum of two weights. Finally, the selection, crossover, and mutation operations of the genetic algorithm were improved using the best reservation selection algorithm and normal distribution crossover operator. Furthermore, an improved legacy algorithm was selected to deal with the multi-objective problem and acquire the optimal solution, that is, the best computing task scheduling scheme. The experimental analysis of the proposed strategy based on the MATLAB simulation platform shows that its energy loss does not exceed 50 J, and the time delay is 23.2 ms, which are better than those of other comparison strategies.

• Journal of Information Technology Services
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• v.16 no.3
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• pp.103-111
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• 2017

The real time scheduling is a key research area in high performance computing and has been a source of challenging problems. A periodic task is an infinite sequence of task instance where each job of a task comes in a regular period. The RMS (Rate Monotonic Scheduling) algorithm has the advantage of a strong theoretical foundation and holds out the promise of reducing the need for exhaustive testing of the scheduling. Many real-time systems built in the past based their scheduling on the Cyclic Executive Model because it produces predictable schedules which facilitate exhaustive testing. In this work we propose hybrid scheduling method which combines features of both of these scheduling algorithms. The original rate monotonic scheduling algorithm didn't consider the uniform sampling tasks in the real time systems. We have enumerated some issues when the RMS is applied to our hybrid scheduling method. We found the scheduling bound for the hard real-time systems which include the uniform sampling tasks. The suggested hybrid scheduling algorithm turns out to have some advantages from the point of view of the real time system designer, and is particularly useful in the context of large critical systems. Our algorithm can be useful for real time system designer who must guarantee the hard real time tasks.

• Industrial Engineering and Management Systems
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• v.11 no.4
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• pp.310-330
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• 2012

Scheduling is an important tool for a manufacturing system, where it can have a major impact on the productivity of a production process. In manufacturing systems, the purpose of scheduling is to minimize the production time and costs, by assigning a production facility when to make, with which staff, and on which equipment. Production scheduling aims to maximize the efficiency of the operation and reduce the costs. In order to find an optimal solution to manufacturing scheduling problems, it attempts to solve complex combinatorial optimization problems. Unfortunately, most of them fall into the class of NP-hard combinatorial problems. Genetic algorithm (GA) is one of the generic population-based metaheuristic optimization algorithms and the best one for finding a satisfactory solution in an acceptable time for the NP-hard scheduling problems. GA is the most popular type of evolutionary algorithm. In this survey paper, we address firstly multiobjective hybrid GA combined with adaptive fuzzy logic controller which gives fitness assignment mechanism and performance measures for solving multiple objective optimization problems, and four crucial issues in the manufacturing scheduling including a mathematical model, GA-based solution method and case study in flexible job-shop scheduling problem (fJSP), automatic guided vehicle (AGV) dispatching models in flexible manufacturing system (FMS) combined with priority-based GA, recent advanced planning and scheduling (APS) models and integrated systems for manufacturing.

• Journal of Korean Institute of Industrial Engineers
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• v.11 no.2
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• pp.155-163
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• 1985

This paper presents a heuristic algorithm for a multidepot aircraft scheduling and crew scheduling with deal-head flights. This algorithm is extended from a Greedy heuristic algorithm for a multi-depot multi-salesman traveling salesman problem. We first transform a given flight schedule into a multi-depot multi-traveling salesman problem, considering aircraft flight policies and crew management constraints. Then we solve this problem by applying a modified Greedy heuristic algorithm.

• IE interfaces
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• v.11 no.3
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• pp.115-128
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• 1998

This paper presents a development of operation scheduling and reactive operation scheduling system for hull fabrication. The methodology for implementing operation scheduling system is HHGA(Hierarchical Hybrid Genetic Algorithm) which exploits both the global perspective of the genetic algorithm and the rapid convergence of the heuristic search for operation scheduling. The methodology for the reactive operation scheduling is the revised HHGA which consists of manual schedule editor for occurrence of exceptional events and the revised scheduling method used in operation scheduling. As the results of experiment, it has been confirmed that HHGA is able to search good operation scheduling within reasonable time, and the revised HHGA is able to search load-balanced reactive operation scheduling with minimum changes of initial operation schedule within short period of time.

• Journal of KIISE:Computer Systems and Theory
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• v.32 no.2
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• pp.68-74
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• 2005

In deadline scheduling, jobs have deadlines by which they are completed. The scheduling algorithm determines which jobs are executed at each time. Then only the completed jobs contribute to the throughput or gain of the algorithm. The jobs have arbitrary weights and the gain of the algorithm is given as the sum of weights of the completed jobs. The goal of the scheduling algorithm is to maximize its gain. In this paper, we consider online non-preemptive scheduling, where jobs arrive online and the scheduling algorithm has no information about jobs arriving ahead. Also the jobs cannot be preempted or rejected while they are executed. For this problem, we obtain lower bounds for any online algorithms and also we propose an optimal online algorithm meeting the lower bounds.