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Dynamic collection scheduling using remote asset monitoring: A case study in the charity sector

Research output: Contribution to journalArticle

  • Fraser McLeod
  • Gunes Erdogan
  • T Cherrett
  • Tolga Bektas
  • Nigel Davies
  • Chris Speed
  • Janet Dickinson
  • S Norgate

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    Rights statement: ©McLeod, F., Erdogan, G., Cherrett, T., Bektas, T., Davies, N., Speed, C., ... Norgate, S. (2014). Dynamic collection scheduling using remote asset monitoring: A case study in the charity sector. Transportation Research Record, 2378, 65-72. 10.3141/2378-07

    Accepted author manuscript, 433 KB, PDF-document

http://trb.metapress.com/content/l722w28w315m1410/?genre=article&id=doi%3a10.3141%2f2378-07
Original languageEnglish
Pages (from-to)65-72
JournalTransportation Research Record
Volume2378
DOIs
Publication statusPublished - 20 Jan 2014

Abstract

In the waste collection sector, remote sensing technology is now coming onto the market, allowing waste and recycling receptacles to report their fill levels at regular intervals. This enables collection schedules to be dynamically optimised to better meet true servicing needs, so reducing transport costs and ensuring that visits to clients are made in a timely fashion. This paper describes a real-life logistics problem faced by a leading UK charity in servicing its textile and book donation banks and its High Street stores using a common fleet of vehicles with varying carrying capacities. This gives rise to a vehicle routing problem whereby visits to stores are on fixed days of the week, with time window constraints, and visits to banks (fitted with remote fill monitoring technology) are made in a timely fashion to avoid them becoming full before collection. A tabu search algorithm was developed to provide vehicles routes for the next day of operation, based on maximising profit. A longer look-ahead period was not considered on the basis that donation rates to banks are highly variable. The algorithm included parameters specifying the minimum fill level (e.g. 50%) required to allow a visit to a bank and a penalty function used to encourage visits to banks that are becoming full. The results showed that the algorithm significantly reduced visits to banks and increased profit by up to 2.4% with best performance obtained the more variable the donation rates.

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