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【明理講堂2023年第98期】12-18北京航空航天大學羅開平副教授:Flexible Process Planning: A Polyhedral Approach Based on Extended OR-Precedence Poset

報告題目:Flexible Process Planning: A Polyhedral Approach Based on Extended OR-Precedence Poset

報告人:北京航空航天大學 羅開平 副教授/支部書記

時間:2023年12月18日上午 9:00-10:00

地點:中關村校區主樓216

報告人簡介:

羅開平,北京航空航天大學經濟偉德國際1946bv官網管理科學與工程系副教授,博士生導師。長期從事最優化理論及其在太空任務管理、商務和金融大數據分析等領域的應用研究,先后主持多項國家自然科學基金項目,參與國家自然科學基金重點項目、重大研究計劃、部級預研項目等,以獨立作者或第一作者在《IEEE Transactions on Cybernetics》、《European Journal of Operational Research》、《Computers & Operations Research》、《International Journal of Production Research》、《系統工程理論與實踐》等國內外知名期刊上發表研究成果50余篇。同時,注重科研成果的落地與轉化,主持多項企事業單位科技委托項目,申請發明專利和軟件著作權近10項。

報告內容簡介:

Flexible Process Planning (FPP) is recognized as the most crucial problem to enable smart/intelligent manufacturing. The existing computer-aided process planning systems have, however, largely relied on meta-heuristic algorithms because of the vast complexity in deriving an optimal solution for the FPP problem. In this paper, we propose to tackle this problem from a distinct perspective, by developing a polyhedral approach based on which nearly optimal solutions can be found in substantially faster time. Specifically, we first cast the FPP problem into two distinct formulations: position assignment and pairwise connection. We then propose a hybrid model to combine the strengths of the two formulations. To improve computational efficiency, we further develop two groups of strong valid inequalities with polynomial cardinality by taking full advantage of the strict partial order of the OR-precedence relation between operations. Our new model with strong valid inequalities yields a significantly tighter linear programming relaxation and a lower computational cost. Our experimental results based on real-world examples indicate that our proposed algorithm designed for the hybrid model performs extraordinarily well in searching for the optimal solution.

(承辦:管理工程系、科研與學術交流中心)

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