Spares parts optimization for legacy telecom networks using a permutation-based evolutionary algorithm

Sid Shakya, Beum Seuk Lee, Carla Di Cairano-Gilfedder, Gilbert Owusu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

Large service organizations such as telecom or utility companies face numerous decision management problems, many of which are related to the management of various resources. The management of spare parts and inventory is one of the key resource management problems an organization faces on a daily basis. Especially their timely availability can have serious impacts on the service quality and the customer satisfaction. Lack of visibility and availability of spare parts in the right place and at the right time can lead to traveling longer distance to supply the parts or in worst case a disruption of the service. We propose to automate the management of spare parts for a legacy technology in a telecom network by leveraging an evolutionary algorithm for optimizing the distribution of spare parts. Our results show that a significant gain can be made in comparison to a assignment typically performed in a manual mechanism.

Original languageBritish English
Title of host publication2017 IEEE Congress on Evolutionary Computation, CEC 2017 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1742-1748
Number of pages7
ISBN (Electronic)9781509046010
DOIs
StatePublished - 5 Jul 2017
Event2017 IEEE Congress on Evolutionary Computation, CEC 2017 - Donostia-San Sebastian, Spain
Duration: 5 Jun 20178 Jun 2017

Publication series

Name2017 IEEE Congress on Evolutionary Computation, CEC 2017 - Proceedings

Conference

Conference2017 IEEE Congress on Evolutionary Computation, CEC 2017
Country/TerritorySpain
CityDonostia-San Sebastian
Period5/06/178/06/17

Keywords

  • Evolutionary algorithms
  • Inventory management
  • Permutation representation
  • Resource management
  • Spare parts management
  • Telecom

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