DM872 (S24)

Mathematical Optimization at Work

General information

Schedule

Odin

Contents

Week Topics and Slides Resources
14 Introduction, Farkas, Interior Point Methods [GRB], [HL, sc 8.4], [MG, sc 7.2], [V, ch 21]; [NW]
  LP Practical Guidelines, Sifting [KN1], [BGLMS, sc 3]
  Practice Sheet 1; sol
15 MILP Practical Guidelines; Presolving; Modeling [KN2], [ABGRW], [Wi, ch7,9,10] or [GRB, modeling 2]
  MILP Formulations for Traveling Salesman Problem [P] or [DFJ] or [MTZ] or [A] or [ABCC] or [OAL]; [OS] [Talk]
  Practice on TSP Sheet 2; sol
16 Lazy Constraints for TSP Sheet 3; sol
  Rounding up the practice on TSP + Dantzig Wolfe decomposition and Delayed Column Generation [GIT]; [BGLMS, sc 3]; [Wo ch 11 in LMS]; [LD]
  Delayed Column Generation; Dual Bounds in Column Generation [Wo ch 11 in LMS]
17 Practice on CG Sheet 4; Sol
  Vehicle Routing: Compact models; Set Partitioning formulation and CG [Fe], [TV];
  Vehicle Routing: Cutting and Branching; Notes on Branching [Wo sc 11.7 in LMS]; [C]; Sheet 5; Assignment 1
18 Surrogate and Lagrangian Relaxations for MILP [Wo ch 10 in LMS]; [Fi]
  Practice on Lagrangian Relaxation Sheet 6; Sol [AMO ch 16 + 17.4 in LMS]
  Further Notes on Lagrangian Relaxation ([IB]; [JB]; [Fi2]); [Fi, sc 8]; [AMO sc 16.4-16.5]; [Wo ch 10 in LMS]
19 Applications: Vehicle Scheduling [BCG]; [CG]
  Crew Scheduling; RCSP [SGSK]; [GM]; Sheet 7
  Integer Programming and Heuristics [Wo ch 13]; [FL]
20 Stochastic Programming [B]; [Wo p 241]; [SP]
  Formulating Equity and Fairness in Optimization Models [CH]
  Practice on Stochastic Programming Sheet 8; sol in [LMS] under Resources
21 Multiobjective optimization [TV], [E] Assignment 2

Further Topics out of curriculum

     
  Benders’ Algorithm; Version 2 [Wo ch 12 in LMS]; [DJ]; [Z];
  Practice on Benders’ Algorithm Sheet 9; Sol; Sol1; Sol2
  Integer Programming and Machine Learning [Wo sc 14.6 in LMS]; [BD]; [FJ]

Code and Data

References

Python

Assessment