系統模擬與基因演算法於完全相同機台排程之應用

阮永漢

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系統模擬與基因演算法於完全相同機台排程之應用

Application of Simulation and Genetic Algorithm to the Identical Machine Scheduling Problem

阮永漢 , Masters　　Advisor：張百棧　　

繁體中文

系統模擬；基因演算法；完全相同機台；多目標； Simulation ； Genetic Algorithm ； Identical Machine ； Multi-Objective

Abstract │ Reference (42) │ Times Cited (16) │ Altmetrics

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The main purpose of this research is to study the application of the Hybrid Algorithm method combined with System Simulation and Genetic Algorithm on 205 Arsenal for the automatic production line system scheduling. It is an Identical Machine Scheduling problem in the 205 Arsenal automatic production line system. There are A, B, C, three production lines that have total of thirteen center complex finishing machines, where A production line has four machines, B production line has five machines, and C production line has four machines. Firstly, system simulation is used to simulate production line to produce MPS. Next, Genetic Algorithm is used to produce day scheduling from MPS. The focus of pervious literature on the complete parallel machine bench scheduling problems was to find optimal solutions under certain single objective evaluation critical. But in practice, we usually face multiple objectives that conflict each other. So the key point is how to achieve a better aggregated objective value under different criteria. This thesis uses the minimum of the sum of maximal Total Flow Time and Makespan as the evaluation standard. In this research, Taguchi experiment design is applied to obtain a better parameter set for Genetic Algorithm within Hybrid Algorithm. The result is then compared to those of SPT, LPT and Genetic Algorithm with different initial solutions. It is shown that the algorithm developed in this research performs better than these heuristics regardless the number of orders.

Reference ( 42 ) 〈TOP〉

1. Allahverdi, A. and J. Mittenthal, “Scheduling on M Parallel Machines Subject to Random Breakdowns to Minimize Expected Mean Flow Time,” Naval Research Logistics, Vol. 41, pp. 677-682, 1994.
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2. Colin, R. R., “A Genetic Algorithm for Flow Shop Sequencing,” Computer Ops Res Vol. l22, No. 1, pp. 5-13, 1995.
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3. Conway, R. W., “Some tractical Problems in digital simulations,” Management Science, Vol. l10, No. 1, pp. 47-61, 1963.
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5. Chen, T. C. E., and Gupta M., “Survey of Scheduling Research Invdving Due Date Determination Decisions,” European Journal of Operational Research, Vol. l38, pp. 156-166, 1989.
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6. Cheng, T. C. E., Z. L. Chen, M. Y. Kovalyov, and Lin B. M. T., “Parallel Machine Batching And Scheduling to Minimize Total Completion Time,” IIE Trans, Vol. 28, No. 11, pp. 953-956, 1996.
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