Order Selection and Capacity Planning in MCS with Chain-to-Chain Collaboration
LI Jizi1, CHEN Ting2, LI Xianxin2 , LIU Chunling21. School of Management, Nanchang University, Nanchang 330031, Jiangxi, China; 2. Department of Mechanic Engineering, Wuhan Textile University, Wuhan 430073, Hubei, China
Due to rejecting order in a single supply chain for lack of adequate capacity, a multi-chain system is introduced to avoid this potential operational risk. Based on four categories of order: direct order, reserve order, chain-to-chain order and rejected order, the framework of order selection in multi-chain system (MCS) is presented, and the model of order selection and planning under chain-to-chain collaboration is formulated. Then, the Lagrange algorithm is used to solve this problem through Lagrange relaxation and decomposition. Finally, numerical study show that opportunity cost of rejecting reserve order and production cost of chain-to-chain order have significant impacts on order selection, and there exists a critical threshold value of the combination of two factors. Through the combination, the multi-chain system can obtain the optimal status, meanwhile manager can utilize this to realize different strategies in MCS.
Key words:multi-chain system(MCS); chain-to-chain collaboration; order selection; Lagrange algorithm
 Hashimu M, Hosain T. Order management in supply chain [J]. Decision Sciences, 2017, 58(1): 567-587.
 Li J, Xiong N, Park J, et al. Intelligent model design of cluster supply chain with horizontal cooperation [J]. Journal of Intelligent Manufacturing, 2012, 23(4): 917-931.
 Sluma T. Model with order acceptance delay in job shop environments [J]. European Journal of Operational Re-search, 2015, 55(3): 211-231.
 Badamu S. Order model with Endogenous quality differentiation in congested markets [J]. Journal of Industrial Management, 2016, 37(9): 622-648.
 Park Q, Gupta O. Prices, delivery time guarantees and capacity selection [J]. Computers and Operations Research, 2016, 21(7): 410-427.
 Tusungi U. Uncertain model with order selection delay[J]. European Journal of Operational Research, 2012, 21(3): 105-125.
 Livtes S. Order acceptance in a supply chain under revenue management [J]. Journal of Copumation and Manufactur-ing Systems, 2016, 18(11): 36-51.
 Slotnick S, Simons L. Order acceptance with information updating[J]. Computers and Operations Research, 2017, 40(1): 3029-3042.
 Chen D, Preach A. Modeling order selection rates and lead-time-related demand [J]. European Journal of Opera-tional Research, 2017, 80(1): 120-138.
 Giggles M. Models with branch-and-price algorithm [J]. Decision Sciences, 2017, 58(3): 611-625.