Enhancing General-Purpose Simulation-Based Optimization Algorithms Via Mixed Integer Linear Programming: A Case Study in Autonomous Ridesharing

Enhancing General-Purpose Simulation-Based Optimization Algorithms Via Mixed Integer Linear Programming: A Case Study in Autonomous Ridesharing

GERAD Research Center via YouTube Direct link

Data-driven Decision Making Under Uncertainty

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4 of 22

Data-driven Decision Making Under Uncertainty

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Enhancing General-Purpose Simulation-Based Optimization Algorithms Via Mixed Integer Linear Programming: A Case Study in Autonomous Ridesharing

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  1. 1 Intro
  2. 2 Urban Mobility and Logistics
  3. 3 Handling Uncertainty
  4. 4 Data-driven Decision Making Under Uncertainty
  5. 5 Discrete Simulation-based Optimization (DSO)
  6. 6 DSO Algorithms
  7. 7 A Nested Partitions (NP) Algorithm
  8. 8 Benchmark Partitioning Rules!
  9. 9 The Dial-a-Ride Problem (DARP)12
  10. 10 The Electric Autonomous Dial-a-Ride Problem13
  11. 11 Event-based DARP for Hardly Constrained Problems
  12. 12 DARP DSO
  13. 13 Event-based Simulator
  14. 14 Partitioning Ideas
  15. 15 Implementation & Benchmark Dataset
  16. 16 DSO Settings
  17. 17 Simulation Example
  18. 18 Solutions from the B&B Tree
  19. 19 Generic Partitioning
  20. 20 Compute Time per Node
  21. 21 Preliminary Results
  22. 22 Next Steps

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