• 국제학술발표논문집
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• The 2th International Conference on Construction Engineering and Project Management
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• pp.739-748
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• 2007

The objective of this research study is to develop the permutation-based genetic algorithm for solving the resource-constrained project scheduling problem in construction engineering by incorporating elitism into genetic algorithm. A key aspect of the algorithm was the development of the elitist roulette selection operator to preserve the best individual solution for the next generation so the improved solution can be obtained. Another notable characteristic is the application of the parallel schedule generation scheme to generate a feasible solution to the problem. Case studies with a standard test problem were presented to demonstrate the performance and accuracy of the algorithm. The computational results indicate that the proposed algorithm produces reasonably good solutions for the resource-constrained project scheduling problem.

• 국제학술발표논문집
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• The 6th International Conference on Construction Engineering and Project Management
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• pp.158-160
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• 2015

Efficient scheduling and resource management are the key factor to reduce construction project budget (e.g., labor cost, equipment cost, material cost, etc.). Resource-based line of balance (LOB) technique has been used to complement the limitations of existing time-driven scheduling techniques (e.g., critical-path method). Optimizing construction alternatives contributes to cost savings while honoring the project deadline. However, existing LOB scheduling is lack of identifying optimal resource combination. This study presents a method which identifies the optimal construction alternatives, hence achieving resource minimization in a repetitive construction by using genetic algorithm (GA). The method provides efficient planning tool that enhances the usability of the system.

• International journal of advanced smart convergence
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• 제12권4호
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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.

• Asia pacific journal of information systems
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• 제27권1호
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• pp.1-17
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• 2017

The need for effective information systems that can help in efficient transportation management has become essential. This study presents the potential benefits of developing a decision support system used by a trucking company for routing and scheduling. Our study investigates how customer exibility factors affect the utilization of transportation resources and establishes a vehicle scheduling model for better allocation of transportation resources with a time window. The results show vehicle savings from 25% up to 70% per day given different levels of exibility in delivery times. Increased capacity utilization can be achieved by considering only customer exibility in the model. Our study implies that incorporating customer exibility into the information system can help transportation organizations have the capability to gain control over management to cut costs and improve service.

• 품질경영학회지
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• 제36권1호
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• pp.40-48
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• 2008

The purpose of this study is to rationally manage service facilities of convention center. This study is to develop the algorithm to consider optimal assignment and optimal operation system planning for convention center. The scheduling algorithm of this study develops through constructing the mathematical model and analyzing the mathematical structure of variables and constraints in model. The scheduling algorithm develops to consist eight stage of optimal operation planning and five stage of optimal assignment planning. Especially, this study indicates that optimum answer through mathematical model and results of algorithm is nondiscrimination.

• International Journal of Computer Science & Network Security
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• 제22권4호
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• pp.310-328
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• 2022

Internet of things (IoT) has emerged as the most popular technique that facilitates enhancing humans' quality of life. However, most time sensitive IoT applications require quick response time. So, processing these IoT applications in cloud servers may not be effective. Therefore, fog computing has emerged as a promising solution that addresses the problem of managing large data bandwidth requirements of devices and quick response time. This technology has resulted in processing a large amount of data near the data source compared to the cloud. However, efficient management of computing resources involving balancing workload, allocating resources, provisioning resources, and scheduling tasks is one primary consideration for effective computing-based solutions, specifically for time-sensitive applications. This paper provides a comprehensive review of the source management strategies considering resource limitations, heterogeneity, unpredicted traffic in the fog computing environment. It presents recent developments in the resource management field of the fog computing environment. It also presents significant management issues such as resource allocation, resource provisioning, resource scheduling, task offloading, etc. Related studies are compared indifferent mentions to provide promising directions of future research by fellow researchers in the field.

• 한국경영과학회지
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• 제13권1호
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• pp.57-57
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• 1988

This paper develops an adaptive scheduling policy for flexible manufacturing systems. The inductive learning methodology used for constructing this state-dependent scheduling policy provides and understanding of the relative importance of the various system parameters in determining the appropriate scheduling rule. Experimental studies indicated the superiority of the suggested approach over the alternative approach involving the repeated application of a single scheduling rule for randomly generated test problems as well as a real system, and under both stationary and nonstationary conditions. In particular, its relative performance improves further when there are frequent disruptions, and when disruptions are caused by the introduction of tiiight due date jobs, one of the most common surces of disruptions in most manufacturing systems.

• 경영과학
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• 제17권2호
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• pp.67-73
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• 2000

This paper describes a scheduling support system for a plant where the machine environment may be modeled as non-identical parallel machine lines (NPML). That is, there are a number of stages in series with various different-capability-machines at each stage. Arriving continuously are jobs with their specific due dates, processing times and candidate processing machines. We’ve developed a real-time scheduling module in conjunction with a supporting production information system which supplies necessary data to the module. This scheduling module is one of the 9 modules in this system, and is composed of both a scheduling interface and a production monitoring interface. This module allows users to generate many candidate schedules by selecting their business policies. The selective arguments which are available consist of allocation costs, batch sizes and machine selection intervals. They are now being implemented at a powder metallurgy plant.

• 경영과학
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• 제28권1호
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• pp.43-52
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• 2011

The basic objective of broadcast scheduling is to get the smallest length TDMA frame, where many nodes are allowed to transmit simultaneously in a single time slot in a conflict-free manner. The secondary objective is to maximize the number of such transmissions for maximum use of the channel. An Artificial Bee Colony (ABC) with ranking strategy is proposed in this paper for the broadcast scheduling problem. Our proposed method is very efficient for generating initial and neighbor feasible solutions. We can get the best number of time slots and transmission utilization comparing to previous researches.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 2007년도 추계학술대회 및 정기총회
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• pp.12-15
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• 2007

Online parallel machine scheduling problems have been studied by many researchers and enormous results are appeared in the last 40 years. With the development of scheduling theory and application, new online scheduling problems where the partial information is known in advance, that is, semi-online, gained much interest due to their increased application in practice. So we consider the online scheduling of three machines with general eligibility and its semi-online variant where the total processing time is known in advance. For the online and semi-online problems, we develop algorithms with competitive ratio of 5/2 which are shown to be optimal.