• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.8
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• pp.3201-3223
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• 2020

Wireless communication has become the promising technology in the recent times because of its applications in Internet of Things( IoT) devices. The IEEE 802.15.4e has become the key technology for IoT devices which utilizes the Time-Slotted Channel Hopping (TSCH) networks for the communication between the devices. In this paper, we develop a Two Level Scheduling Algorithm (TLSA) for scheduling multiple packets with different arrival rate at the source nodes in a TSCH networks based on the link activated by a centralized scheduler. TLSA is developed by considering three types of links in a network such as link i with packets arrival type 1, link j with packets arrival type 2, link k with packets arrival type 3. For the data packets arrival, two stages in a network is considered.At the first stage, the packets are considered to be of higher priority.At the second stage, the packets are considered to be of lower priority.We introduce level 1 schedule for the packets at stage 1 and level 2 schedule for the packets at stage 2 respectively. Finally, the TLSA is validated with the two different energy functions i.e., y = e^ax - 1 and y = 0.5x² using MATLAB 2017a software for the computation of average and worst ratios of the two levels.

• Journal of the Korean Operations Research and Management Science Society
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• v.41 no.2
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• pp.129-139
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• 2016

This paper presented a robust ship scheduling model using the quadratic programming problem. Given a set of available carriers under control and a set of cargoes to be transported from origin to destination, a robust ship scheduling that can minimize the mean-variance objective function with the required level of profit can be modeled. Computational experiments concerning relevant maritime transportation problems are performed on randomly generated configurations of tanker scheduling in bulk trade. In the first stage, the optimal transportation problem to achieve maximum revenue is solved through the traditional set-packing model that includes all feasible schedules for each carrier. In the second stage, the robust ship scheduling problem is formulated as mentioned in the quadratic programming. Single index model is used to efficiently calculate the variance-covariance matrix of objective function. Significant results are reported to validate that the proposed model can be utilized in the decision problem of ship scheduling after considering robustness and the required level of profit.

• Management Science and Financial Engineering
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• v.12 no.1
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• pp.95-112
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• 2006

Disassembly scheduling is the problem of determining the quantity and timing of disassembling used or end-of-life products while satisfying the demand of their parts and/or components over a planning horizon. The case of assembly product structure is considered while the resource capacity constraints are explicitly considered. A cost-based objective is considered that minimizes the sum of disassembly operation and inventory holding costs. The problem is formulated as an integer programming model, and a two-stage heuristic with construction and improvement algorithms is suggested in this paper. To test the performance of the heuristic, computational experiments are done on randomly generated problems, and the results show that the heuristic gives near optimal solutions within a very short amount of computation time.

• Journal of Korean Institute of Industrial Engineers
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• v.12 no.2
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• pp.33-44
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• 1986

This research is concerned with group scheduling problems in multi-stage manufacturing system with dependent setup time. The objective of the research is to develop and evaluate a heuristic algorithm for determining group sequence and job sequence within each group to minimize total tardiness in multi-stage manufacturing systems with sequence dependent group setup time. The group scheduling heuristic algorithm is developed and evaluated by comparisons with twenty-seven problems with the known optimum solutions and 144,000 random schedules of a large variety problems. The results indicate that the proposed heuristic algorithm gets the same optimum solutions for the problems and also provides the good solutions in comparison with the random schedules of the large variety problems. A numerical example is given to illustrate the heuristic algorithm.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.26 no.4
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• pp.63-71
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• 2003

This paper analyses a deterministic scheduling problem concerned with manufacturing multiple types of components at a pre-assembly stage composed of parallel fabrication machines. Each component part is machined on a fabrication machine specified in advance. The manufactured components are subsequently assembled into products. The completion time of a job(product) is measured by the latest completion time of its all components at the pre-assembly stage. The problem has the objective measure of minimizing the total weighted completion time of a finite number of jobs. Two lower bounds are derived and tested in a branch-and-bound scheme. Also, three constructive heuristic algorithms are developed based on the machine aggregation and greedy strategies. Some empirical evaluation of the performance of the proposed branch-and-bound and heuristic algorithms are also performed.

• Journal of Korean Institute of Industrial Engineers
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• v.9 no.1
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• pp.23-31
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• 1983

A group scheduling problem, which is production scheduling problem associated with the concept of group technology, is studied under due date constraints in multi-stage manufacturing systems. The purpose of this paper is to develop and evaluate a practical heuristic procedure for determining group sequence and job sequence within each group to minimize total tardiness in multi-stage manufacturing systems. A heuristic algorithm has been developed by introducing the concept of relative measures of job tardiness and group tardiness for job sequencing and group sequencing, respectively. A numerical example is shown to illustrate the proposed procedure. The heuristic algoirthm is tested by comparisons with problems with known optimal solutions and also with random group schedules for a set of large-size problems. Results indicate that the proposed heuristic algorithm provides good solutions with small computational requirements, and thus is viable for large size problems in practice.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.29 no.4
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• pp.34-42
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• 2006

This paper considers an assembly-type flowshop scheduling problem in which each job is assembled with two types of components. One type of the components is outsourced with positive lead time but the other type is fabricated in-house at the first stage. The two types of the components should be prepared at the first stage before starting the assembly operation for each job at the second stage. The objective is to schedule the jobs so that the makespan is minimized. Some solution properties and lower bounds are derived and incorporated into a branch and bound algorithm. Also, an efficient heuristic is developed. The performances of the proposed branch and bound algorithm and heuristic are evaluated through computational experiments.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.3
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• pp.551-569
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• 2024

With the rapid development of electric vehicles (EVs) industry, EV charging service becomes more and more important. Especially, in the case of suddenly drop of air temperature or open holidays that large-scale EVs seeking for charging devices (CDs) in a short time. In such scenario, inefficient EV charging scheduling algorithm might lead to a bad service quality, for example, long queueing times for EVs and unreasonable idling time for charging devices. To deal with this issue, this paper propose a Deep-Q-Network (DQN) based two-stage scheduling method for the large-scale EVs charging service. Fine-grained states with two delicate neural networks are proposed to optimize the sequencing of EVs and charging station (CS) arrangement. Two efficient algorithms are presented to obtain the optimal EVs charging scheduling scheme for large-scale EVs charging demand. Three case studies show the superiority of our proposal, in terms of a high service quality (minimized average queuing time of EVs and maximized charging performance at both EV and CS sides) and achieve greater scheduling efficiency. The code and data are available at THE CODE AND DATA.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.11 no.1
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• pp.65-70
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• 2011

The increased disk rotational velocity to improve the data transfer rate has raised up many serious problems in its servo control system which should control the position and velocity of a spot relative to a rotating disk. This paper proposes gain-scheduling-based track-seek control for single stage actuator of hard disk drives. Gain scheduling is a technique that can extend the validity of the linearization approach to a range of operating points and one of the most popular approaches to nonlinear control design. The proposed method schedules controller gains to improve the transient response and minimize overshoot during the functions of the read/write head positioning servomechanism for the seek control. The validity of the proposed method is demonstrated through stability analysis and simulation results.

• Journal of the Korean Operations Research and Management Science Society
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• v.33 no.3
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• pp.1-16
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• 2008

This paper considers a scheduling problem to minimize the total tardiness in the two-stage assembly-type flowshop. The system is composed of multiple fabrication machines in the first stage and a final-assembly machine in the second stage. Each job consists of multiple tasks, each task is performed on the fabrication machine specified in advance. After all the tasks of a job are finished, the assembly task can be started on the final-assembly machine. The completion time of a job is the time that the assembly task for the job is completed. The objective of this paper is to find the optimal schedule minimizing the total tardiness of a group of jobs. In the problem analysis, we first derive three solution properties to determine the sequence between two consecutive jobs. Moreover, two lower objective bounds are derived and tested along with the derived properties within a branch-and-bound scheme. Two efficient heuristic algorithms are also developed. The overall performances of the proposed properties, branch-and-bound and heuristic algorithms are evaluated through numerical experiments.