A Random Forest-Enhanced Genetic Algorithm for Order Acceptance Scheduling with Past-Sequence-Dependent Setup Times
學年 113
學期 2
出版（發表）日期 2025-03-15
作品名稱 A Random Forest-Enhanced Genetic Algorithm for Order Acceptance Scheduling with Past-Sequence-Dependent Setup Times
作品名稱（其他語言）
著者 陳世興; CHEN; SHIH-HSIN; Wang; Yu-Chen; Liu; Ming-Hsiang; Chang; Chih-Wei
單位
出版者
著錄名稱、卷期、頁數 Computers & Operations Research 162, pp.106-118
摘要 This paper proposes a novel hybrid approach combining Random Forest machine learning techniques with Genetic Algorithms to solve the order acceptance and scheduling problem with past-sequence-dependent setup times. The Random Forest component helps predict optimal scheduling patterns, while the Genetic Algorithm optimizes the overall solution. Experimental results demonstrate superior performance compared to traditional methods in terms of computational efficiency and solution quality.
關鍵字 genetic algorithm; random forest; order acceptance; scheduling; setup times; optimization
語言 en_US
ISSN 0305-0548
期刊性質 國外
收錄於 SCI
產學合作
通訊作者
審稿制度 是
國別 TWN
公開徵稿
出版型式 ,電子版
相關連結

機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/128046 )