書誌事項
- タイトル別名
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- Estimation of Weighting Factors for Multi-Objective Scheduling Problems using Input-Output Data
- ニュウシュツリョク データ オ モチイタ タモクテキ スケジューリング モンダイ ノ オモミ ケイスウ スイテイ
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抄録
<p>Scheduling problems are widely used in recent production systems. In order to model a production scheduling problem more effectively, it is necessary to build a mathematical modeling technique that automatically generates an appropriate schedule instead of an actual human operator. This paper addresses two types of model estimation methods for weighting factors in the multi-objective scheduling problems from input-output data. The one is a machine learning-based method, and the other one is the parameter estimation method based on an inverse optimization. These methods are applied to three-objectives parallel machine scheduling problems, whose objective functions consist of makespan, the weighted sum of completion time, the weighted sum of tardiness, the weighted sum of earliness and tardiness, and setup costs. The accuracy of the proposed machine learning and inverse optimization methods is evaluated. A surrogate model that learns input-output data is proposed to reduce the computational efforts. Computational results show the effectiveness of the proposed method for weighting factors in the objective function from the optimal solutions.</p>
収録刊行物
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- システム制御情報学会論文誌
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システム制御情報学会論文誌 35 (1), 1-9, 2022-01-15
一般社団法人 システム制御情報学会
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詳細情報 詳細情報について
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- CRID
- 1390010457640529664
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- NII論文ID
- 40022794846
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- NII書誌ID
- AN1013280X
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- ISSN
- 2185811X
- 13425668
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- NDL書誌ID
- 031913644
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- 本文言語コード
- ja
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- データソース種別
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- JaLC
- NDL
- Crossref
- CiNii Articles
- KAKEN
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- 抄録ライセンスフラグ
- 使用不可