• Journal of applied mathematics & informatics
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• v.26 no.5_6
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• pp.889-900
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• 2008

The problem of scheduling n jobs on a single machine is considered when the machine is subject to stochastic breakdowns. The objective is to minimize the weighted squared deviation of job completion times from a common due date. Two versions of the problem are addressed. In the first one the common due date is a given constant, whereas in the second one the common due date is a decision variable. In each case, a general form of deterministic equivalent of the stochastic scheduling problem is obtained when the counting process N(t) related to the machine uptimes is a Poisson process. It is proved that an optimal schedule must be V-shaped in terms of weighted processing time when the agreeable weight condition is satisfied. Based on the V-shape property, two dynamic programming algorithms are proposed to solve both versions of the problem.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2002.05a
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• pp.704-708
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• 2002

Production scheduling has been one of the most critical issues in a manufacturing environment Job-shop scheduling problems(JSP) are well know from the standpoint of production planning and operations control in this research scheduling against due date is a measure of performance and the objective is minimizing total weighted tardiness This paper presents an idea of decomposition of the problem and shows robustmess of the schedule under various disturbances along with exact and approximation methods. The proposed method can indeed handle shop disturbances more effectively when compared with traditional and dynamic scheduling methods.

• Proceedings of the Korea Society for Simulation Conference
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• 1999.10a
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• pp.100-107
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• 1999

무인 운반차량 시스템 (AGV System) 의 이용도가 날로 증가함에 따라 시스템의 최적화 및 운영 방법에 관한 많은 연구가 진행되고 있다. 이에 본 연구에서는 AGV System에서 사용하는 Routing 및 Scheduling 정책들을 연구하고 이를 개선할 수 있는 새로운 방안을 모색한 후, 컴퓨터 모델링 기법을 이용한 보다 객관적인 시뮬레이션을 수행하여 최적의 AGV System과 그에 적합한 운영 정책을 제시하는데 그 목적이 있다. 따라서 본 논문은 크게 AGV Routing 과 Scheduling에 관한 연구로 나누어진다. AGV Routing은 AGV의 이동경로를 설정하는 것으로서 충돌 방지 (Collision Avoidance)와 최단경로 탐색 (Minimal Cost Path Find) 이라는 두 개의 주요 알고리즘으로 이루어진다. AGV Scheduling 은 장비의 공정시간과 AGV의 Loading/Unloading, Charging 시간으로 인해 불규칙한 Event 가 일어났을 경우 AGV 각각의 Jop을 알맞게 선정해주는 정책을 말하며 일반적으로 AGV Selection Rule, Charging Rule이 여기에 속한다. 본 연구에서는 이러한 알고리즘들이 반영된 AGV System을 컴퓨터 모델로 구축하여, 기존 시스템에서 사용되고 있는 여러 운영 정책들의 문제점들을 분석하였으며, Multiple AGV System을 최적화 시키는 운영 정책이 보다 객관적으로 제시되었다.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.22 no.53
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• pp.23-35
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• 1999

Since on-time delivery is becoming increasingly important in today's competitive markets, the development of effective scheduling methodologies to meet customer needs through on time delivery is of vital importance for the well-being of companies. The objective of this study is to develope a general heuristic algorithm for scheduling both the static and dynamic problems under certain on-time delivery criteria. For the problems with due-date related, we present insights for minimizing the number of tardy jobs and propose a heuristic scheduling algorithm. Experimental results show that the proposed algorithm performs significantly better than other dispatching rules within reasonable computation time, specially in the environment of strong competition for resources.

• Journal of Information Processing Systems
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• v.7 no.4
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• pp.707-716
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• 2011

It is important that desktop grids should be able to aggressively deal with the dynamic properties that arise from the volatility and heterogeneity of resources. Therefore, it is required that task scheduling be able to positively consider the execution behavior that is characterized by an individual resource. In this paper, we implement a log analysis system with REST web services, which can analyze the execution behavior by utilizing the actual log data of desktop grid systems. To verify the log analysis system, we conducted simulations and showed that the resource group-based task scheduling, based on the analysis of the execution behavior, offers a faster turnaround time than the existing one even if few resources are used.

• Proceedings of the KIEE Conference
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• 1998.11a
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• pp.289-291
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• 1998

This paper presents short-term hydro scheduling method for hydrothermal coordination by genetic algorithm. Hydro scheduling problem has many constraints with fixed final reservoir volume. In this paper, the difficult water balance constraints caused by hydraulic coupling satisfied throughout dynamic decoding method. Adaptive penalizing method was also proposed to handle the infeasible solutions that violate various constraints. The effectiveness of proposed method in this paper was examined through the case studies. Further studies for the validation of the hydro scheduling scheme obtained by genetic algorithm will be very appreciated.

• Proceedings of the Korean Information Science Society Conference
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• 2010.06c
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• pp.118-121
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• 2010

The dynamic nature and exponential growth of the World Wide Web remain crawling important pages early still challenging. State-of-the-art crawl scheduling algorithms require huge running time to prioritize web pages during crawling. In this research, we proposed crawl scheduling algorithms that are not only fast but also download important pages early. The algorithms give high importance to some specific pages those have good linkages such as inlinks from different domains or host. The proposed algorithms were experimented on publically available large datasets. The results of experiments showed that propagating more importance to the inter-host links improves the effectiveness of crawl scheduling than the current state-of-the-art crawl scheduling algorithms.

• International journal of advanced smart convergence
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• v.12 no.4
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• pp.126-133
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• 2023

Recent advancements in cloud service virtualization technologies have witnessed a shift from a Virtual Machine-centric approach to a container-centric paradigm, offering advantages such as faster deployment and enhanced portability. Container orchestration has emerged as a key technology for efficient management and scheduling of these containers. However, with the increasing complexity and diversity of heterogeneous workloads and service types, resource scheduling has become a challenging task. Various research endeavors are underway to address the challenges posed by diverse workloads and services. Yet, a systematic approach to container orchestration for effective cloud management has not been clearly defined. This paper proposes the DRA-Engine (Dynamic Resource Allocation Engine) for resource scheduling in container orchestration. The proposed engine comprises the Request Load Procedure, Required Resource Measurement Procedure, and Resource Provision Decision Procedure. Through these components, the DRA-Engine dynamically allocates resources according to the application's requirements, presenting a solution to the challenges of resource scheduling in container orchestration.

• Journal of the Korea Society of Computer and Information
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• v.13 no.1
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• pp.29-35
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• 2008

For efficient message passing of Parallel programs, it is required to schedule the involved two processes at the same time which are executed on different nodes, that is called 'co-scheduling' However, each node of cluster systems is built on top of general purpose multitasking OS. which autonomously manages local Processes. Thus it is not so easy to co-schedule two (or more) processes in such computing environment. Our work proposes a co-scheduling scheme for MPI-based parallel programs which exploits message exchange information between two parties. We implement the scheme on Linux cluster which requires slight kernel hacking and MPI library modification. The experiment with NPB parallel suite shows that our scheme results in 33-56% reduction in the execution time compared to the typical scheduling case. and especially better Performance in more communication-bound applications.

• Proceedings of the Korea Society for Simulation Conference
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• 1997.04a
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• pp.93-99
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• 1997

Most of the past studies on FMS scheduling problems may be classified into two classes, namely off-line scheduling and on-line scheduling approach. The off-line scheduling methods are used mostly for FMS planning purposes and may not be useful real time control of FMSs, because it generates solutions only after a relatively long period of time. The on-line scheduling methods are used extensively for dynamic real-time control of FMSs although the performance of on-line scheduling algorithms tends vary dramatically depending on various configurations of FMS. Current study is about finding a better on-line scheduling rules for FMS operations. In this study, we propose a method to create priority functions that can be used in setting relative priorities among jobs or machines in on-line scheduling. The priority functions reflect the configuration of FMS and the user-defined objective functions. The priority functions are generated from diverse dispatching rules which may be considered a special priority functions by themselves, and used to determine the order of processing and transporting parts. Overall system of our work consists of two modules, the Priority Function Evolution Module (PFEM) and the FMS Simulation Module (FMSSM). The PFEM generates new priority functions using input variables from a terminal set and primitive functions from a function set by genetic programming. And the FMSSM evaluates each priority function by a simulation methodology. Based on these evaluated values, the PFEM creates new priority functions by using crossover, mutation operation and probabilistic selection. These processes are iteratively applied until the termination criteria are satisfied. We considered various configurations and objective functions of FMSs in our study, and we seek a workable solution rather than an optimum or near optimum solution in scheduling FMS operations in real time. To verify the viability of our approach, experimental results of our model on real FMS are included.