Hedging against demand ambiguity in new product development: a two-stage distributionally robust approach

Yuanbo Li1,2, Meiyan Lin3, Houcai Shen2, Lianmin Zhang2,4
1School of Management, Nanjing University of Posts and Telecommunications, Nanjing, People’s Republic of China
2School of Management and Engineering, Nanjing University, Nanjing, People’s Republic of China
3College of Management, Shenzhen University, Shenzhen, People’s Republic of China
4Shenzhen Research Institute of Big Data, Shenzhen, People’s Republic of China

Tóm tắt

In the globalization era, many manufacturing companies face great uncertainties, as most components in new product development (NPD) are outsourced to external and internal suppliers worldwide. More seriously, component supply chain disruptions have been seen in the recent global outbreak of COVID-19. Hence, some key components must be reserved in advance to control risks considering the suppliers’ production plans and uncertain lead time. We propose a key components reservation model for NPD concerning component commonality and substitution. Demand is characterized by a scenario-wise ambiguity set consisting of mean, support, and mean absolute deviation information. Based on a demand unsatisfied index (DUI), we establish a two-stage distributionally robust optimization (DRO) model, which is reformulated to a linear programming (LP) model by duality analysis and solved by a proposed column and constraints generation (CCG) algorithm. We examine the performance of the DRO model over other benchmark models. The proposed DRO model with DUI has a lower probability and magnitude for demand shortage. The scenario-wise ambiguity set also outperforms the single-scenario and deterministic models, especially when product demand varies inconsistently in different scenarios. The proposed CCG algorithm can significantly improve the solution procedure for large-scale problems.

Tài liệu tham khảo

Bai, Q., Xu, J., & Zhang, Y. (2020). The distributionally robust optimization model for a remanufacturing system under cap-and-trade policy: A newsvendor approach. Annals of Operations Research, 309(2), 731–760. Balakrishnan, A., & Geunes, J. (2000). Requirements planning with substitutions: Exploiting bill-of-materials flexibility in production planning. Manufacturing & Service Operations Management, 2(2), 166–185. Ben-Tal, A., & Nemirovski, A. (1998). Robust convex optimization. Mathematics of Operations Research, 23(4), 769–805. Ben-Tal, A., & Nemirovski, A. (1999). Robust solutions of uncertain linear programs. Operations Research Letters, 25(1), 1–13. Ben-Tal, A., & Nemirovski, A. (2000). Robust solutions of linear programming problems contaminated with uncertain data. Mathematical Programming, 88(3), 411–424. Ben-Tal, A., Nemirovski, A., & Roos, C. (2002). Robust solutions of uncertain quadratic and conic-quadratic problems. SIAM Journal on Optimization, 13(2), 535–560. Bernstein, F., Kök, A. G., & Xie, L. (2011). The role of component commonality in product assortment decisions. Manufacturing & Service Operations Management, 13(2), 261–270. Bertsimas, D., Farias, V., & Trichakis, N. (2011). The price of fairness. Operations Research, 59(1), 17–31. Bertsimas, D., Pachamanova, D., & Sim, M. (2004). Robust linear optimization under general norms. Operations Research Letters, 32(6), 510–516. Bertsimas, D., & Sim, M. (2004). The price of robustness. Operations Research, 52(1), 35–53. Breuer, D. J., Kapadia, S., Lahrichi, N., & Benneyan, J. C. (2022). Joint robust optimization of bed capacity, nurse staffing, and care access under uncertainty. Annals of Operations Research, 312(2), 673–689. Cao, Y., Li, D., Zhang, Y., Tang, Q., Khodaei, A., Zhang, H., & Han, Z. (2022). Optimal energy management for multi-microgrid under a transactive energy framework with distributionally robust optimization. IEEE Transactions on Smart Grid, 13(1), 599–612. Chen, L. G., Long, D. Z., & Perakis, G. (2015). The impact of a target on newsvendor decisions. Manufacturing & Service Operations Management, 17(1), 78–86. Chen, Z., Sim, M., & Xiong, P. (2020). Robust stochastic optimization made easy with RSOME. Management Science, 66(8), 3329–3339. Cheng, C., Adulyasak, Y., & Rousseau, L.-M. (2021). Robust facility location under disruptions. INFORMS Journal on Optimization, 3(3), 298–314. Chern, C.-C., Lei, S.-T., & Huang, K.-L. (2012). Solving a multi-objective master planning problem with substitution and a recycling process for a capacitated multi-commodity supply chain network. Journal of Intelligent Manufacturing, 25(1), 1–25. Chern, C.-C., & Yang, I.-C. (2011). A heuristic master planning algorithm for supply chains that consider substitutions and commonalities. Expert Systems with Applications, 38(12), 14918–14934. Chow, V. T. F., Cui, Z., & Long, D. Z. (2022). Target-oriented distributionally robust optimization and its applications to surgery allocation. INFORMS Journal on Computing, 34(4), 2058–2072. Conejo, A. J., Hall, N. G., Long, D. Z., & Zhang, R. (2021). Robust capacity planning for project management. INFORMS Journal on Computing, 33(4), 1533–1550. Cooper, R. G. (1990). Stage-gate systems: A new tool for managing new products. Business Horizons, 33(3), 44–54. Cooper, R. G., & Kleinschmidt, E. J. (2010). Success factors for new-product development. John Wiley & Sons Ltd. Cui, Z., Ding, J., Long, D. Z., & Zhang, L. (2022). Target-based resource pooling problem. Production and Operations Management, 32(4), 1187–1204. Cui, Z., Long, D. Z., Qi, J., & Zhang, L. (2023). The inventory routing problem under uncertainty. Operations Research, 71(1), 378–395. Deshpande, V., Cohen, M. A., & Donohue, K. (2003). A threshold inventory rationing policy for service-differentiated demand classes. Management Science, 49(6), 683–703. Deza, A., Huang, K., Liang, H., & Wang, X. J. (2017). On component commonality for periodic review assemble-to-order systems. Annals of Operations Research, 265(1), 29–46. Ding, J., Chen, L., Ke, G. Y., Li, Y., & Zhang, L. (2021). Balancing the profit and capacity under uncertainties: A target-based distributionally robust knapsack problem. International Transactions in Operational Research, 29(2), 760–782. Eynan, A. (1996). The impact of demands’ correlation on the effectiveness of component commonality. International Journal of Production Research, 34(6), 1581–1602. Fisher, M., Ramdas, K., & Ulrich, K. (1999). Component sharing in the management of product variety: A study of automotive braking systems. Management Science, 45(3), 297–315. Freeman, N. K., Narayanan, A., & Keskin, B. B. (2021). Optimal use of downward substitution in a manufacturing operation subject to uncertainty. Omega, 103, 102372. Gerchak, Y., Magazine, M. J., & Gamble, A. B. (1988). Component commonality with service level requirements. Management Science, 34(6), 753–760. Geunes, J. (2003). Solving large-scale requirements planning problems with component substitution options. Computers & Industrial Engineering, 44(3), 475–491. Hajebrahimi, A., Kamwa, I., Abdelaziz, M. M. A., & Moeini, A. (2020). Scenario-wise distributionally robust optimization for collaborative intermittent resources and electric vehicle aggregator bidding strategy. IEEE Transactions on Power Systems, 35(5), 3706–3718. Hajebrahimi, A., Kamwa, I., Delage, E., & Abdelaziz, M. M. A. (2020). Adaptive distributionally robust optimization for electricity and electrified transportation planning. IEEE Transactions on Smart Grid, 11(5), 4278–4289. Hall, N. G., Long, D. Z., Qi, J., & Sim, M. (2015). Managing underperformance risk in project portfolio selection. Operations Research, 63, 660–675. Heese, H. S., & Swaminathan, J. M. (2006). Product line design with component commonality and cost-reduction effort. Manufacturing & Service Operations Management, 8(2), 206–219. Hillier, M. S. (1999). Component commonality in a multiple-period inventory model with service level constraints. International Journal of Production Research, 37(12), 2665–2683. Huang, Y.-S., Lo, H.-W., & Ho, J.-W. (2018). Effects of component commonality and perishability on inventory control in assemble-to-order systems. Operational Research, 21(1), 205–229. Korhonen, T., Laine, T., Lyly-Yrjänäinen, J., & Suomala, P. (2016). Innovation for multiproject management: The case of component commonality. Project Management Journal, 47(2), 130–143. Kwapisz, J., Infante, V., & Cameron, B. G. (2019). Commonality opportunity search in industrial product portfolios. International Journal of Technology Management, 81(3/4), 258. Labro, E. (2004). The cost effects of component commonality: A literature review through a management-accounting lens. Manufacturing & Service Operations Management, 6(4), 358–367. Lang, J. C., & Domschke, W. (2008). Efficient reformulations for dynamic lot-sizing problems with product substitution. OR Spectrum, 32(2), 263–291. Li, Y., Cui, Z., Shen, H., & Zhang, L. (2021). Target-based project crashing problem by adaptive distributionally robust optimization. Computers & Industrial Engineering, 157, 107160. Li, Y., Kuo, Y.-H., Li, R., Shen, H., & Zhang, L. (2022). A target-based distributionally robust model for the parallel machine scheduling problem. International Journal of Production Research, 60(22), 6728–6749. Liu, N., Chow, P.-S., & Zhao, H. (2019). Challenges and critical successful factors for apparel mass customization operations: Recent development and case study. Annals of Operations Research, 291(1–2), 531–563. Liu, W., Yang, L., & Yu, B. (2021). KDE distributionally robust portfolio optimization with higher moment coherent risk. Annals of Operations Research, 307(1–2), 363–397. Long, D. Z., Qi, J., & Zhang, A. (2023). Supermodularity in two-stage distributionally robust optimization. Management Science. https://doi.org/10.1287/mnsc.2023.4748 Mieghem, J. A. V. (2004). Note-commonality strategies: Value drivers and equivalence with flexible capacity and inventory substitution. Management Science, 50(3), 419–424. Mirchandani, P., & Mishra, A. K. (2009). Component commonality: Models with productspecific service constraints. Production and Operations Management, 11(2), 199–215. Pei, Z., Lu, H., Jin, Q., & Zhang, L. (2022). Target-based distributionally robust optimization for single machine scheduling. European Journal of Operational Research, 299(2), 420–431. Rao, U. S., Swaminathan, J. M., & Zhang, J. (2004). Multi-product inventory planning with downward substitution, stochastic demand and setup costs. IIE Transactions, 36(1), 59–71. Simchi-Levi, D., Wang, H., & Wei, Y. (2019). Constraint generation for two-stage robust network flow problems. INFORMS Journal on Optimization, 1(1), 49–70. Teunter, R. H., & Kuipers, S. (2022). Inventory control with demand substitution: New insights from a two-product economic order quantity analysis. Omega, 113, 102712. Wang, X., Kuo, Y.-H., Shen, H., & Zhang, L. (2021). Target-oriented robust location–transportation problem with service-level measure. Transportation Research Part B: Methodological, 153, 1–20. Xiao, Y., & Zhang, H. (2021). New product advantage infused by modularity: Do resources make a difference? Journal of Product Innovation Management, 38(4), 473–493. Xidonas, P., Steuer, R., & Hassapis, C. (2020). Robust portfolio optimization: A categorized bibliographic review. Annals of Operations Research, 292(1), 533–552. Zeng, B., & Zhao, L. (2013). Solving two-stage robust optimization problems using a column-and-constraint generation method. Operations Research Letters, 41(5), 457–461.