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551. Production Network Design under Supply Uncertainty
Invited abstract in session WD-55: Supply Chain Network Optimization, stream Transportation.
Wednesday, 14:30-16:00Room: S02 (building: 101)
Authors (first author is the speaker)
| 1. | Michel Fender
|
| Africa Business School, Mohammed VI Polytechnic University | |
| 2. | Nadia Jaoui
|
| Africa Business School, Mohammed VI Polytechnic University | |
| 3. | Nizar El Hachemi
|
| Africa Business School, Mohammed VI Polytechnic University | |
| 4. | Walid Klibi
|
| Operations Management and Information Systems Department, KEDGE Business School |
Abstract
Our research addresses a production network design problem involving strategic decisions related to selecting production site locations and their capacities, choosing suppliers, and sizing an internal fleet of vehicles and/or engaging external transportation providers. The problem also considers tactical decisions regarding flows between origin-destination pairs, produced quantities, and inventory levels. These decisions are made within a dynamic environment considering uncertainty in suppliers and production capacities, as well as the availability of transportation vehicles. The problem's structure allows us to model it as a multi-stage stochastic model. However, we approximate it as a two-stage model where strategic decisions are made at the first stage, while tactical ones are set as second-stage decisions. To solve various instances of our problem, we assess the efficiency of three resolution methods: Cplex's default branch-and-cut algorithm, Cplex's Benders decomposition, and partial Benders decomposition. Next, we demonstrate the relevance of integrating the three strategic decisions instead of making them separately and study the impact of different degrees of uncertainty on these decisions. Our findings justify that partial Benders decomposition produces high-quality solutions while achieving computational efficiency, highlighting the suitability of the stochastic model and the resolution approach for dealing with practical supply chain applications.
Keywords
- Supply Chain Management
- Network Design
- Stochastic Optimization
Status: accepted
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