• Journal of the Korea Safety Management & Science
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• v.25 no.2
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• pp.1-8
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• 2023

This paper is proposing a novel machine scheduling model for the unrelated parallel machine scheduling problem without setup times to minimize the total completion time, also known as "makespan". This problem is a NP-complete problem, and to date, most approaches for real-life situations are based on the operator's experience or simple heuristics. The new model based on the Memetic Algorithm, which was proposed by P. Moscato in 1989, is a hybrid algorithm that includes genetic algorithm and local search optimization. The new model is tested on randomly generated datasets, and is compared to optimal solution, and four scheduling models; three rule-based heuristic algorithms, and a genetic algorithm based scheduling model from literature; the test results show that the new model performed better than scheduling models from literature.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.141-144
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• 2003

This paper proposes an analytical model of off-line feed rate scheduling to obtain an optimum feed rate for high speed machining. Off-line feed rate scheduling is presented as an advanced technology to regulate cutting forces through change of feed per tooth, which directly affects variation of uncut chip thickness. In this paper, the feed rate scheduling model was developed using a mechanistic cutting force model using cutting-condition-independent coefficients. First, it was verified that cutting force coefficients are not changed with respect to cutting speed. Thus, the feed rate scheduling model using the cutting-condition-independent coefficients can be applied to set the proper feed rates for high speed machining as well as normal machining. Experimental results show that the developed fred rate scheduling model makes it possible to maintain the cutting force at a desired level during high speed machining.

• Proceedings of the Korea Society for Simulation Conference
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• 2005.05a
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• pp.29-33
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• 2005

Grid computing is widely applicable to various fields of industry including process control and manufacturing, military command and control, transportation management, and so on. In a viewpoint of application area, grid computing can be classified to three aspects that are computational grid, data grid and access grid. This paper focuses on computational grid which handles complex and large-scale computing problems. Computational grid is characterized by system dynamics which handles a variety of processors and jobs on continuous time. To solve problems of system complexity and reliability due to complex system dynamics, computational grid needs scheduling policies that allocate various jobs to proper processors and decide processing orders of allocated jobs. This paper proposes the service prediction-based job scheduling model and present its algorithm that is applicable for computational grid. The service prediction-based job scheduling model can minimize overall system execution time since the model predicts a processing time of each processing component and distributes a job to processing component with minimum processing time. This paper implements the job scheduling model on the DEVSJAVA modeling and simulation environment and simulates with a case study to evaluate its efficiency and reliability Empirical results, which are compared to the conventional scheduling policies such as the random scheduling and the round-robin scheduling, show the usefulness of service prediction-based job scheduling.

• Korean Journal of Construction Engineering and Management
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• v.12 no.1
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• pp.23-32
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• 2011

Domestic leading construction companies has been establishing and performing TACT scheduling method, similar to linear scheduling model such as line of balance and repetitive schedule, and etc. in which repetitive construction works are involved like high-rise building. Linear scheduling model has been researched as a visual scheduling method presenting the work space and time information. Likewise scheduling constraints of CPM network such as finish-to-finish, start-to-start, finish-to-start, start-to-start, linear scheduling model also has the relationships constraints, namely boundary conditions, between activities. It is especially necessary to define the boundary conditions of the activities' relationships in order to apply the linear scheduling model to be compatible with the network schedule. Therefore, this research considers the boundary conditions between activities for establishing the linear scheduling model. This paper also applies the proposed boundary conditions to TACT schedule and then deduces the main considerations in order to establish and perform TACT schedule.

• International conference on construction engineering and project management
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• 2005.10a
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• pp.744-747
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• 2005

The AEC (Architecture/Engineering/Construction) industry is facing a competitive world after it entered into the 21^st century. Due to improper planning and scheduling, the construction projects face severe delays in completion. Most of the present day construction organisations operate in multiple project environments where more than one projects are to be managed simultaneously. But the advantages of planning and scheduling as multiple projects have not been utilized by these organisations. Change in multi-project planning and scheduling is inevitable and often frequent, therefore the traditional planning and scheduling approaches are no more feasible in scheduling multiple construction projects. The traditional scheduling tools like CPM and PERT do not offer any help in scheduling in a resource-constrained environment. This necessitated a detailed study to model the environment realistically and to make the allocation of limited resources flexible and efficient. This paper delineates about the proactive model which will help the project managers for scheduling the multiple construction projects.

• Journal of Navigation and Port Research
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• v.30 no.7
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• pp.561-566
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• 2006

In this paper, we propose a new ship scheduling set packing model considering limited risk or variance. The set packing model is used in many applications, such as vehicle routing, crew scheduling, ship scheduling, cutting stock and so on. As long as the ship scheduling is concerned, there exits many unknown external factors such as machine breakdown, climate change and transportation cost fluctuation. However, existing ship scheduling models have not considered those factors apparently. We use a quadratic set packing model to limit the variance of expected cost of ship scheduling problems under stochastic spot rates. Set problems are NP-complete, and additional quadratic constraint makes the problems much harder. We implement Kelley's cutting plane method to replace the hard quadratic constraint by many linear constrains and use branch-and-bound algorithm to get the optimal integral solution. Some meaningful computational results and comments are provided.

• International conference on construction engineering and project management
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• 2005.10a
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• pp.917-923
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• 2005

Scheduling is one of the main functions in construction project to determine the sequence of activities necessary to complete a project. The scheduling techniques provide important information crucial to a project's success. Highway construction project the paving activity can be considered a linear activity. Linear scheduling technique may be better suited for linear projects than other scheduling techniques. A new type of scheduling in linear project is calling Linear Scheduling Model (LSM). The Project monitoring and controlling is very ease to identify that all the stage of linear project and have more advantages.

• Journal of the Korea Society for Simulation
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• v.15 no.4
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• pp.129-136
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• 2006

Grid computing has been appeared for solving large-scaled data which are not solved by a single computer. Grid computing is a new generation platform which connects geographically distributed heterogeneous resources. However, gathering heterogeneous distributed resources produces many difficult problems. Especially. to assure resource reliability is one of the most critical problems. So, we propose a grid resource scheduling model using grid resource reliability measurement. We evaluate resource reliability based on resource status data and apply it to the grid scheduling model in DEVSJAVA modeling and simulation. This paper evaluates parameters such as resource utilization, job loss and average turn-around time and estimates experiment results of our model in comparison with those of existing scheduling models such as a random scheduling model and a round-robin scheduling model. These experiment results showed that the resource reliability measurement scheduling model provides efficient resource allocation and stable Job processing in comparison with a random scheduling model and a round-robin scheduling model.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.1
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• pp.1-8
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• 2009

This paper aims mainly to reinterpretate Optimal Bus Scheduling Model by applying System Dynamics Perspective. Traditionally, the study regarding Optimal Bus Scheduling Model stems on the linear relationshp. However, this paper attempted to convert linear relationship based Optimal Bus Scheduling Model to causal loop perspective based Model. In result, the paper present Casual Loop Diagram for Optimal Bus Scheduling Model. Furthermore, the paper also ran a simulation based on Stock & Flow Diagram for Optimal Bus Scheduling Model. The outcome was not much different from the linear relationship based Model due to the similarity of the equation applied on two models.

• Journal of the Korea Society for Simulation
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• v.14 no.3
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• pp.91-100
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• 2005

Grid computing is widely applicable to various fields of industry including process control and manufacturing, military command and control, transportation management, and so on. In a viewpoint of application area, grid computing can be classified to three aspects that are computational grid, data grid and access grid. This paper focuses on computational grid which handles complex and large-scale computing problems. Computational grid is characterized by system dynamics which handles a variety of processors and jobs on continuous time. To solve problems of system complexity and reliability due to complex system dynamics, computational grid needs scheduling policies that allocate various jobs to proper processors and decide processing orders of allocated jobs. This paper proposes a service prediction-based job scheduling model and present its scheduling algorithm that is applicable for computational grid. The service prediction-based job scheduling model can minimize overall system execution time since the model predicts the next processing time of each processing component and distributes a job to a processing component with minimum processing time. This paper implements the job scheduling model on the DEVS modeling and simulation environment and evaluates its efficiency and reliability. Empirical results, which are compared to conventional scheduling policies, show the usefulness of service prediction-based job scheduling.