• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.05a
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• pp.1124-1132
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• 2006

This paper considers a flow shop scheduling problem where a different WIP (work-in-process) state has different weight on the duration time. The objective is to minimize the sum of the weighted WIP. For the two machine flow shop case, the recognition version is unary NP-Complete. The three simple and intuitive heuristics H0, H1, and H2 are presented for the problem. For each heuristic, we find an upper bound on relative error which is tight in limit. For heuristic H2, we show that H2 dominates the other two heuristics.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10b
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• pp.1250-1255
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• 1990

This paper discusses an optimal cyclic scheduling problem for a FMC (Flexible Manufacturing Cell) modeled by a two-machine flowshop with two machining centers with APC's (Automated Pallet Changers), an AGV (Automated Guided Vehicle) and loading and unloading stations. Cyclic production in which similar patterns of production is repeated can significantly reduce the production lead-time and WIP (Work-In-Process) in such flexible, automated system. Thus we want to find an optimal cyclic schedule that minimizes the cycle time in each cycle. However, the existence of APC's as buffer storage for WIP makes the problem intractable (i.e., NP-complete). We propose an practical approximation algorithm that minimizes, instead of each cycle time, its upper bound. Performances of this algorithm are validated by the way of computer simulations.

• Journal of the Korean Operations Research and Management Science Society
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• v.30 no.1
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• pp.27-41
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• 2005

This paper considers identical parallel machine scheduling problem. Each job has a processing time. due date. weight and family type. If a different type of job is followed by prior job. a family setup is incurred. A two phased heuristic is presented for minimizing the sum of weighted tardiness. In the first phase. using roiling horizon technique. group each job into same family and schedule each family. In the second phase. assign each job to machines using schedule obtained in the first phase. Extensive computational experiments and comparisons among other algorithms are carried out to show the efficiency of the proposed algorithm.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.43 no.3
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• pp.492-503
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• 1994

In this study, the control and scheduling of the flexible manufacturing cell (FMC) is discussed, which can perform the mixed production and relieve the effect of machine failure. The control of the FMC isvery complex task due to the property of multiple jobs and the dynamically changing states. For effective control of proposed FMC, the hierarchical scheme is introduced and the functions of each levels are defined. Especially for the control functions of shop floor level and cell level, the intelligent scheduler is implemented. To show the efficiency of the intelligent scheduler, the production method fo the existing assembly lines was evaluated and compared with the proposed intelligent FMC method. The results from the production performance show that the proposed method is superior to the existing method in various performance indices.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.30 no.1
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• pp.115-121
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• 2007

In this paper, we study flowshop scheduling problems with availability constraints. In such problems, n jobs have to be scheduled on m machines sequentially under assumption that the machines are unavailable during some periods of planning horizon. The objective of the problem is to find a non-permutation schedule which minimizes the makespan. As a solution procedure, we propose an improved genetic algorithm which utilizes a look-ahead schedule generator to find good solutions in a reasonable time Computational experiments show that the proposed genetic algorithm outperforms the existing genetic algorithm.

• The Journal of Bigdata
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• v.5 no.1
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• pp.189-195
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• 2020

We consider the stale problem which makes the training speed slow in the field of deep learning. The problem can be formulated as a single-machine scheduling problem with generalized due dates in which the objective is to minimize the total earliness and tardiness. We show that the problem can be solved in polynomial time if the orders of the small and the large jobs in an optimal schedule are known in advance.

• Journal of the Korea Society of Computer and Information
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• v.21 no.9
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• pp.91-100
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• 2016

In this research, emergency vehicle dispatching problems faced with in the wake of massive natural disasters are considered. Here, the emergency vehicle dispatching problems can be regarded as a single machine stochastic scheduling problems, where the processing times are independently and identically distributed random variables, are considered. The objective of minimizing the expected number of tardy jobs, with distinct job due dates that are independently and arbitrarily distributed random variables, is dealt with. For these problems, optimal static-list policies can be found by solving corresponding assignment problems. However, for the special cases where due dates are exponentially distributed random variables, using a proposed dynamic programming approach is found to be relatively faster than solving the corresponding assignment problems. This so-called Pivot Dynamic Programming approach exploits necessary optimality conditions derived for ordering the jobs partially.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.24 no.62
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• pp.97-109
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• 2001

This research is concerned with jobshop scheduling problem for an advanced manufacturing system like flexible manufacturing which consists of two machine centers and a single automated guided vehicle(AGV). The objective is to develop and evaluate heuristic scheduling procedures that minimize makespan to be included travel time of AGV. A new heuristic algorithm is proposed and illustrates the proposed algorithm. The heuristic algorithm is implemented for various cases by SLAM II. The results show that the proposed algorithm provides better solutions in reduction ratio and frequency than the previous algorithm.

• Journal of Korean Institute of Industrial Engineers
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• v.25 no.2
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• pp.254-265
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• 1999

We consider two stage hybrid flowshop scheduling problem when there are two non-identical parallel machines at the first stage, and only one machine at the second stage. Several well-known sequence-first allocate-second heuristics are considered first. We then propose an allocate-first sequence-second heuristic to find minimum makespan schedule. The effectiveness of the proposed heuristic algorithm in finding a minimum makespan schedule is empirically evaluated by comparing with easily computable lower bound. The proposed heuristic algorithm as well as the existing heuristics are evaluated by simulation in four cases which have different processing time distribution, and it is found that the proposed algorithm is more effective in every case.

• Journal of Korean Society for Quality Management
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• v.22 no.3
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• pp.161-178
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• 1994

FMS are being installed to improve productivity, manufacturing consistency and flexibility. However, FMS are quite expensive and efforts must be made to avoid the high investment risk. The objective of this paper is to enable the real-time rescheduling under dynamic changes in FMS environment. For this purpose, a KBSS (Knowledge-Based Scheduling System) in FMS environment is developed. This KBSS will meet various requirements of users, for example, to minimize makespan, average flow time, or to maximize machine utilization.