• Journal of Institute of Control, Robotics and Systems
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• v.9 no.9
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• pp.727-735
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• 2003

The determination of completion time constitutes an important step in developing algorithms for short-term production scheduling. Existing completion time algorithms of multi-product batch processes often assume that intermediate storage tanks are always available when it is needed. In this paper, we consider a serial multi-product batch plants with ZW and NIS policy intermediate storge tank. We limit storage residence time and allocated products in the intermediate storage tank to minimize the quality change of the stored material as well as to reduce the clearing time during product change. A set of recurrence relations is suggested to calculate the completion times for the given batch sequence of products on all processing units. Also analytic solution for the suggested model is solved by a graphical method. The effectiveness of these results is proved by a few illustrative examples.

• The Transactions of the Korea Information Processing Society
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• v.6 no.5
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• pp.1203-1211
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• 1999

Checkpointing is the one of fault-tolerant techniques to restore faults and to restart job fast. Checkpointing algorithms in distributed systems have been studied for many years. These algorithms can be classified into synchronous Checkpointing algorithms and asynchronous Checkpoiting algorithms. In this paper, we propose an independent Checkpointing algorithm that has a minimum Checkpointing counts equal to periodic Checkpointing algorithm, and relatively short rollback distance at faulty situation. Checkpointing count is directly related to task completion time in a fault-free situation and short rollback distance is directly related to task completion time in a faulty situation. The proposed algorithm is compared with the previously proposed asynchronous Checkpointing algorithms using simulation. In the simulation, the proposed Checkpointing algorithm produces better results than other algorithms in terms of task completion time in fault-free as well as faulty situations.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.47 no.2
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• pp.48-56
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• 2024

We examine a single machine scheduling problem with step-improving jobs in which job processing times decrease step-wisely over time according to their starting times. The objective is to minimize total completion time which is defined as the sum of completion times of jobs. The total completion time is frequently considered as an objective because it is highly related to the total time spent by jobs in the system as well as work-in-progress. Many applications of this problem can be observed in the real world such as data gathering networks, system upgrades or technological shock, and production lines operated with part-time workers in each shift. Our goal is to develop a scheduling algorithm that can provide an optimal solution. For this, we present an efficient branch and bound algorithm with an assignment-based node design and tight lower bounds that can prune branch and bound nodes at early stages and accordingly reduce the computation time. In numerical experiments well designed to consider various scenarios, it is shown that the proposed algorithm outperforms the existing method and can solve practical problems within reasonable computation time.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1993.04a
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• pp.343-352
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• 1993

In this study, a modified algorithm for the exchange heuristic is developed and applied to a resource-constrained scheduling problem. The problem involves multiple projects and multiple resource categories and allows flexible resource allocation to each activity. The objective is to minimize the maximum completion time. The exchange heuristkc is a multiple pass algorithm which makes improvements upon a given initial feasible schedule. Four different modified algorithms are proposed. The original algorithm and the new algorithms were compared through an experimental investigation. All the proposed algorithms reduce the maximum completion time much more effectively than the original algorithm. Especially, one of four proposed algorithms obviously outperforms the other three algorithms. The algorithm of the best performance produces significantly shorter schedules than the original algorithm, though it requires up to three times more computation time. However, in most situations, a reduction in schedule length means a significant reduction in the total cost.

• Industrial Engineering and Management Systems
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• v.10 no.4
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• pp.247-254
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• 2011

In this paper, we study a single-machine scheduling problem with deteriorating processing time of jobs and multiple rate-modifying activities which reset deteriorated processing time to the original processing time. In this situation, the objective function is to minimize total completion time. First, we formulate an integer programming model. Since the model is difficult to solve as the size of real problem being very large, we design an improved genetic algorithm called adaptive genetic algorithm (AGA) with spontaneously adjusting crossover and mutation rate depending upon the status of current population. Finally, we conduct some computational experiments to evaluate the performance of AGA with the conventional GAs with various combinations of crossover and mutation rates.

• Proceedings of the KIEE Conference
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• 1987.07a
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• pp.288-292
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• 1987

The purpose of this paper is to develope the parallel computation algorithm that enables it to minimize the completion tine of computation execution of the entire subtasks, under the constraints of the series-parallel precedence relation in each subtask. The developed algorithm was applied to the control of a robot manipulator functioned by multi-CPU's and to obtain the minimum time schedule so that real time control may be achieved. The completion time of computation execution was minimized by applying "Variable" Branch and Bound algorithm which was developed In this paper in determining the optimum ordered schedule for each CPU.

• IE interfaces
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• v.24 no.4
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• pp.281-294
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• 2011

This paper considers the rail crane scheduling problem which is defined as determining the sequence of loading/unloading container on/from a freight train. The objective is to minimize the weighted sum of the range of order completion time and makespan. The range of order completion time implies the difference between the maximum of completion time and minimum of start time of each customer order consisting of jobs. Makespan refers to the time when all the jobs are completed. In a rail freight terminal, logistics firms as a customer wish to reduce the range of their order completion time. To develop a methodology for the crane scheduling, we formulate the problem as a mixed integer program and develop three metaheuristics, namely, genetic algorithm, simulated annealing, and tabu search. To validate the effectiveness of heuristic algorithms, computational experiments are done based on a set of real life data. Results of the experiments show that heuristic algorithms give good solutions for small-size and large-size problems in terms of solution quality and computation time.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.29 no.1
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• pp.1-8
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• 2006

This paper proposes a real-time resource allocation algorithm for minimizing the completion time of overall workflow process. The jobs in a workflow process are interrelated through the precedence graph including Sequence, AND, OR and Loop control structure. A resource should be allocated for the processing of each job, and the required processing time of the job can be varied by the resource allocation decision. Each resource has several inherent restrictions such as the functional, geographical, positional and other operational characteristics. The algorithm suggested in this paper selects an effective resource for each job by considering the precedence constraint and the resource characteristics such as processing time and the inherent restrictions. To investigate the performance of the proposed algorithm, several numerical tests are performed for four different workflow graphs including standard, parallel and two series-parallel structures. In the tests, the solutions by the proposed algorithm are compared with random and optimal solutions which are obtained by a random selection rule and a full enumeration method respectively.

• Journal of the Korea Society of Computer and Information
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• v.22 no.10
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• pp.101-107
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• 2017

In this paper, we study the problem of parallel machine scheduling considering the moving time of multiple servers. The parallel machine scheduling is to assign jobs to parallel machines so that the total completion time(makespan) is minimized. Each job has a setup phase, a processing phase and a removal phase. A processing phase is performed by a parallel machine alone while a setup phase and a removal phase are performed by both a server and a parallel machine simultaneously. A server is needed to move to a parallel machine for a setup phase and a removal phase. But previous researches have been done under the assumption that the server moving time is zero. In this study we have proposed an efficient algorithm for the problem of parallel machine scheduling considering multiple server moving time. We also have investigated experimentally how the number of servers and the server moving time affect the total completion time.

• Journal of information and communication convergence engineering
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• v.17 no.4
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• pp.279-284
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• 2019

This paper presents processing-node status-based message scattering and gathering algorithms for multi-processor systems on chip to reduce the communication time between processors. In the message-scattering part of the message-passing interface (MPI) scatter function, data transmissions are ordered according to the proposed linear algorithm, based on the processor status. The MPI hardware unit in the root processing node checks whether each processing node's status is 'free' or 'busy' when an MPI scatter message is received. Then, it first transfers the data to a 'free' processing node, thereby reducing the scattering completion time. In the message-gathering part of the MPI gather function, the data transmissions are ordered according to the proposed linear algorithm, and the gathering is performed. The root node receives data from the processing node that wants to transfer first, and reduces the completion time during the gathering. The experimental results show that the performance of the proposed algorithm increases at a greater rate as the number of processing nodes increases.