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1
Intro
2
Summary of the SPDPL
3
One-Warehouse Multi-Retailer Problems
4
Production-Routing Problems
5
Dual Sourcing
6
Summary of the literature
7
Decomposition of the time periods.
8
Rolling horizon framework to take the decisions
9
SPDPL multi-stage static-dynamic model
10
Dynamic programming
11
Branch and cut
12
Flow-based guiding heuristic
13
Flow improvement sub-problem
14
Instances
15
Comparisons with CPLEX
16
Value of stochastic solutions
17
Scenario trees to sample randomness
18
Impact of the scenario tree
19
Generalizing the transportation modes
20
Preliminary experiments
21
Conclusion
Description:
Explore a tree-search heuristic for stochastic production-distribution planning with transportation mode-dependent lead times in this 48-minute seminar from GERAD Research Center. Delve into the complex problem of simultaneous production and transportation decisions, including selecting optimal transportation modes for shipping goods to customers. Learn about the trade-offs between shorter lead times, higher costs, and increased flexibility in reacting to demand changes. Examine the multi-stage problem with a discrete finite time horizon and stochastic customer demand, solved using a rolling horizon framework and static-dynamic problem representation. Discover the tree-search heuristic based on Anytime Column Search and Limited Discrepancy Search, featuring a node selection strategy that aggregates scenarios for efficient solution improvement. Gain insights into decomposition of time periods, dynamic programming, branch and cut techniques, flow-based guiding heuristics, and the impact of scenario trees on stochastic solutions. Read more

A Tree-Search Heuristic for Stochastic Production-Distribution Planning with Transportation Mode-Dependent Lead Times

GERAD Research Center
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