A Genetic Algorithm for Truck Dispatching in Mining

14 pages•Published: October 19, 2017

Wesley Cox, Tim French, Mark Reynolds and Lyndon While

Abstract

We apply genetic algorithms (GAs) to evolve cyclic finite automata for scheduling the dispatch of trucks in mines. The GA performs well generally, and on problems which include one-lane roads, the GA was able to find solutions that utilised shovels very well, with low contention and using fewer trucks than both the widely-used linear programming DISPATCH algorithm, and commonly-used greedy heuristics. The GA provides significant cost-savings, or production increases, on problems where alternative algorithms do not adapt well.

Keyphrases: automata, genetic algorithms, scheduling

In: Christoph Benzmüller, Christine Lisetti and Martin Theobald (editors). GCAI 2017. 3rd Global Conference on Artificial Intelligence, vol 50, pages 93-106.

Links:	https://easychair.org/publications/paper/3PFP
	https://doi.org/10.29007/n11t

BibTeX entry

@inproceedings{GCAI2017:Genetic_Algorithm_Truck_Dispatching,
  author    = {Wesley Cox and Tim French and Mark Reynolds and Lyndon While},
  title     = {A Genetic Algorithm for Truck Dispatching in Mining},
  booktitle = {GCAI 2017. 3rd Global Conference on Artificial Intelligence},
  editor    = {Christoph Benzmüller and Christine Lisetti and Martin Theobald},
  series    = {EPiC Series in Computing},
  volume    = {50},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2398-7340},
  url       = {/publications/paper/3PFP},
  doi       = {10.29007/n11t},
  pages     = {93-106},
  year      = {2017}}

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