Bi-level programming for joint order acceptance and production planning in industrial robot manufacturing enterprise

被引:0
|
作者
Zhang, Mingyu [1 ]
Kong, Min [1 ,2 ]
Shi, Houbo [1 ]
Tan, Weimin [1 ]
Fathollahi-Fard, Amir M. [3 ,4 ,6 ]
Yaseen, Zaher Mundher [5 ]
机构
[1] Anhui Normal Univ, Sch Econ & Management, Wuhu 241000, Peoples R China
[2] Hefei Univ Technol, Sch Management, Hefei 230009, Peoples R China
[3] Macao Univ Sci & Technol, Fac Innovat Engn, Dept Engn Sci, Taipa 999078, Macau, Peoples R China
[4] Al Ayen Univ, Sci Res Ctr, New Era & Dev Civil Engn Res Grp, Nasiriyah 64001, Thi Qar, Iraq
[5] King Fahd Univ Petr & Minerals, Civil & Environm Engn Dept, Dhahran 31261, Saudi Arabia
[6] Univ Quebec Montreal, Dept Analyt Operat & Technol Informat, BP 8888,Succ Ctr Ville, Montreal, PQ H3C 3P8, Canada
基金
中国国家自然科学基金; 中国博士后科学基金;
关键词
Industrial robot; Order acceptance; Production planning; Bi-level programming; Meta-heuristic Algorithm; MACHINES;
D O I
10.1016/j.cie.2024.110471
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Effectively addressing the Order Acceptance and Production Planning (OAP) problem is crucial for industrial robot manufacturers, particularly considering the rapid expansion of the industrial robot market. A bi-level programming model is structured to enhance synergies in response to department reformation within an industrial robot manufacturer. The upper-level model focuses on order acceptance, considering rejection and delay penalty costs, aiming to maximize enterprise profit. The lower-level model concentrates on product production, aiming to minimize the total sum of production costs and Work-In-Progress (WIP) holding costs. Detailed constraints related to material readiness, including inventory levels and procurement lead times, are comprehensively examined. Given the NP-hard complexity of this multi-objective problem, a meta-heuristic algorithm Whale Optimization Algorithm (WOA) is implemented. To enhance WOA's optimization capabilities, two heuristic algorithms, Solution Improvement policy (I-algorithm) and Heuristic-based acceleration strategy (H-algorithm), are introduced, resulting in the development of WOA-IH. The experimental evidence suggests that the proposed model facilitates decision coordination for manufacturers, particularly in order management, production planning, and material procurement. Furthermore, this study contributes to applying bi-level programming theory in managing supply chains for industrial robotics.
引用
收藏
页数:20
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