• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.1
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• pp.39-60
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• 2017

In the Cloud, for the scheduling of parallel jobs, there are many tasks in a job and those tasks are executed concurrently on different VMs (Visual machines), where each task of the job will be executed synchronously. The goal of scheduling is to reduce the execution time and to keep the fairness between jobs to prevent some jobs from waiting more time than others. We propose a Cloud model which has multiple Clouds, and under this model, jobs are in different lists according to the waiting time of the jobs and every job has different parallelism. At the same time, a new method-ZOMT (the scheduling parallel tasks based on ZERO-ONE scheduling with multiple targets) is proposed to solve the problem of scheduling parallel jobs in the Cloud. Simulations of ZOMT, AFCFS (Adapted First Come First Served), LJFS (Largest Job First Served) and Fair are executed to test the performance of those methods. Metrics about the waiting time, and response time are used to test the performance of ZOMT. The simulation results have shown that ZOMT not only reduces waiting time and response time, but also provides fairness to jobs.

• Journal of the Korean Society for Precision Engineering
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• v.31 no.8
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• pp.689-696
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• 2014

This paper presents a scheduling problem for a high-density robotic workcell using multi-objective genetic algorithm. We propose a new algorithm based on NSGA-II(Non-dominated Sorting Algorithm-II) which is the most popular algorithm to solve multi-objective optimization problems. To solve the problem efficiently, the proposed algorithm divides the problem into two processes: clustering and scheduling. In clustering process, we focus on multi-robot positions because they are fixed in manufacturing system and have a great effect on task distribution. We test the algorithm by changing multi-robot positions and compare it to previous work. Test results shows that the proposed algorithm is effective under various conditions.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.4
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• pp.1100-1122
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• 2023

Scheduling user-submitted cloud tasks to the appropriate virtual machine (VM) in cloud computing is critical for cloud providers. However, as the demand for cloud resources from user tasks continues to grow, current evolutionary algorithms (EAs) cannot satisfy the optimal solution of large-scale cloud task scheduling problems. In this paper, we first construct a large- scale multi-objective cloud task problem considering the time and cost functions. Second, a multi-objective optimization algorithm based on multi-factor optimization (MFO) is proposed to solve the established problem. This algorithm solves by decomposing the large-scale optimization problem into multiple optimization subproblems. This reduces the computational burden of the algorithm. Later, the introduction of the MFO strategy provides the algorithm with a parallel evolutionary paradigm for multiple subpopulations of implicit knowledge transfer. Finally, simulation experiments and comparisons are performed on a large-scale task scheduling test set on the CloudSim platform. Experimental results show that our algorithm can obtain the best scheduling solution while maintaining good results of the objective function compared with other optimization algorithms.

• Journal of Korean Institute of Industrial Engineers
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• v.35 no.4
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• pp.257-265
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• 2009

This paper considers the hybrid flow shop scheduling problem for the objective of minimizing the number of tardy jobs. In hybrid flow shops, each job is processed through multiple production stages in series, each of which has multiple identical parallel machines. The problem is to determine the allocation of jobs to the parallel machines at each stage as well as the sequence of the jobs assigned to each machine. Due to the complexity of the problem, we suggest search heuristics, tabu search and simulated annealing algorithms with a new method to generate neighborhood solutions. In particular, to evaluate and select neighborhood solutions, three surrogate objectives are additionally suggested because not much difference in the number of tardy jobs can be found among the neighborhoods. To test the performances of the surrogate objective based search heuristics, computational experiments were performed on a number of test instances and the results show that the surrogate objective based search heuristics were better than the original ones. Also, they gave the optimal solutions for most small-size test instances.

• Journal of Korean Institute of Industrial Engineers
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• v.38 no.4
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• pp.262-275
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• 2012

This paper develops a multistage scheduling algorithm for the module operation of the LCD(Liquid Crystal Display) production systems and tests the efficiency of the proposed algorithm. The module operation is a multistage form composed of multiple sub operations of processes, and each stage is consists of multiple lines with the same kinds of machines. This paper presents a mathematical modeling reflecting the constraints of the LCD module operation and develops a multistage scheduling algorithm based on tabu search metaheuristic approach. For this purpose, an production order is assigned to a line of the sub operations and a sequence of the assigned order is rearranged to draw an efficient schedule. Simulation experiments test performance measures and show the efficiency of the proposed algorithm.

• IE interfaces
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• v.12 no.4
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• pp.617-624
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• 1999

In order to maximize an availability of machine and utilization of space, the parallel machines scheduling problem with space limit is frequently discussed in the industrial field. In this paper, we consider a scheduling problem for assembly machine in ship engine assembly shop. This paper considers the parallel machine scheduling problem in which n jobs having different release times, due dates and space limits are to be scheduled on m parallel machines. The objective function is to minimize the sum of earliness and tardiness. To solve this problem, a heuristic is developed. The proposed heuristic is divided into three modules hierarchically: job selection, machine selection and job sequencing, solution improvement. To illustrate its effectiveness, a proposed heuristic is evaluated with a large number of randomly generated test problems based on the field situation. Through the computational experiment, we determine the job selection rule that is suitable to the problem situation considered in this paper and show the effectiveness of our heuristic.

• Industrial Engineering and Management Systems
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• v.10 no.1
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• pp.74-83
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• 2011

In this paper, we consider a new lot-sizing and scheduling problem (LSSP) that minimizes the sum of production cost, setup cost and inventory cost. Setup carry-over, setup overlapping, state dependent setup time as well as demand splitting are considered. For this LSSP, we develop a mixed integer programming (MIP) model, of which the size does not increase even if we divide a time period into a number of micro time periods. Also, we develop an efficient heuristic algorithm by combining a decomposition scheme with a local search procedure. Test results show that the developed heuristic algorithm finds a good quality (in practice, even better) feasible solution using far less computation time compared with the CPLEX, a competitive MIP solver.

• Journal of Multimedia Information System
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• v.1 no.2
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• pp.95-100
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• 2014

Variable message signs (VMS) have the different sizes and a specific type according to the city scene and it has to be displayed by different message on the display panel in real-time. And VMS manufacturers must produce the different products in order to give a customized product to each order. In addition that, they should test and check the correct operation to each VMS product using the different message frame. That is very time and workers consuming and VMS emulator with an automatic variable message generator system is necessary. Also, the automatic message generator system is needed to real-time scheduling in order to display the message on the VMS panel like real world. In this paper, we design and implement the VMS emulator embedded the automatic message frame generator system with real-time scheduling which can set several parameters easily on the windows dialog.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.35 no.1
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• pp.79-86
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• 2012

This study focuses on the problem of scheduling wafer lots of several recipe(operation condition) types in the photolithography workstation in a semiconductor wafer fabrication facility, and sequence-dependent recipe set up times may be required at the photolithography machines. In addition, a lot is able to be operated at a machine when the reticle(mask) corresponding to the recipe type is set up in the photolithography machine. We suggest various heuristic algorithms, in which developed recipe selection rules and lot selection rules are used to generate reasonable schedules to minimizing the total weighted flowtime. Results of computational tests on randomly generated test problems show that the suggested algorithms outperform a scheduling method used in a real manufacturing system in terms of the total weighted flowtime of the wafer lots with ready times.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.11
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• pp.1892-1902
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• 2007

This paper presents a new generating unit maintenance scheduling algorithm considering regional reserve margin and transfer capability. Existing researches focused on reliability of the overall power systems have some problems that adequate reliability criteria cannot be guaranteed in supply shortage regions. Therefore specific constraints which can treat regional reserve ratio have to be added to conventional approaches. The objective function considered in this paper is the variance (second-order momentum) of operating reserve margin to levelize reliability during a planning horizon. This paper focuses on significances of considering regional reliability criteria and an advanced hybrid optimization method based on PSO algorithm. The proposed method has been applied to IEEE reliability test system(1996) with 32-generators and a real-world large scale power system with 291 generators. The results are compared with those of the classical central maintenance scheduling approaches and conventional PSO algorithm to verify the effectiveness of the algorithm proposed in this paper.