Algorithms

This chapter describes some used algorithms.

References

An incomplete list of important references:

  • Clarke, G & Wright, JW 1964: Scheduling of vehicles from a Central Depot to a Number of the Delivery Point. Operations Research, 12 (4): 568-581

  • Pisinger, David; Røpke, Stefan: A general heuristic for vehicle routing problems

  • Schrimpf, G., Schneider, K., Stamm-Wilbrandt, H., Dueck, V.: Record Breaking Optimization Results Using the Ruin and Recreate Principle. J. of Computational Physics 159 (2000) 139–171

  • Jan Christiaens, Greet Vanden Berghe: Slack Induction by String Removals for Vehicle Routing Problems

  • Thibaut Vidal: Hybrid Genetic Search for the CVRP: Open-Source Implementation and SWAP* Neighborhood

  • Richard F. Hartl, Thibaut Vidal: Workload Equity in Vehicle Routing Problems: A Survey and Analysis

  • K. Deb; A. Pratap; S. Agarwal; T. Meyarivan: A fast and elitist multiobjective genetic algorithm: NSGA-II

  • Damminda Alahakoon, Saman K Halgamuge, Srinivasan Bala: Dynamic self-organizing maps with controlled growth for knowledge discovery

  • Daniel J. Russo, Benjamin Van Roy, Abbas Kazerouni, Ian Osband and Zheng Wen: A Tutorial on Thompson Sampling https://web.stanford.edu/~bvr/pubs/TS_Tutorial.pdf

  • Florian Arnold, Kenneth Sörensen: What makes a solution good? The generation of problem-specific knowledge for heuristics

  • Flavien Lucas, Romain Billot, Marc Sevaux: A comment on "what makes a VRP solution good? The generation of problem-specific knowledge for heuristics"

  • Erik Pitzer, Michael Affenzeller: A Comprehensive Survey on Fitness Landscape Analysis