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European Journal of Operational Research
- Publication Year :
- 2021
- Publisher :
- Elsevier, 2021.
-
Abstract
- This work studies a Robust Multi-product Newsvendor Model with Substitution (R-MNMS), where the demand and the substitution rates are stochastic and are subject to cardinality-constrained uncertainty sets. The goal of this work is to determine the optimal order quantities of multiple products to maximize the worst-case total profit. To achieve this, we first show that for given order quantities, computing the worst-case total profit, in general, is NP-hard. Therefore, we derive the closed-form optimal solutions for the following three special cases: (1) if there are only two products, (2) if there is no substitution among different products, and (3) if the budget of demand uncertainty is equal to the number of products. For a general R-MNMS, we formulate it as a mixed-integer linear program with an exponential number of constraints and develop a branch and cut algorithm to solve it. For large-scale problem instances, we further propose a conservative approximation of R-MNMS and prove that under some certain conditions, this conservative approximation yields an exact optimal solution to R-MNMS. The numerical study demonstrates the effectiveness of the proposed approaches and the robustness of our model. Accepted version
- Subjects :
- Mathematical optimization
Technology
Operations Research
Information Systems and Management
General Computer Science
Linear programming
0211 other engineering and technologies
Social Sciences
Stochastic programming
02 engineering and technology
Management Science and Operations Research
Newsvendor model
Industrial and Manufacturing Engineering
Profit (economics)
Business & Economics
Robust
0502 economics and business
Mixed-integer program
Cardinality-constrained uncertainty set
Mathematics
050210 logistics & transportation
021103 operations research
Operations Research & Management Science
05 social sciences
Multi product
Management
Modeling and Simulation
Exponential number
Branch and cut algorithm
Branch and cut
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Accession number :
- edsair.doi.dedup.....a032343fc663f94a87bcaa500d9c1aa9