Multi-Objective Human Resource Allocation Approach for Sustainable Traffic Management.

Soumendra Nath Sanyal, Izabela Nielsen, Subrata Saha
Author Information
  1. Soumendra Nath Sanyal: Department of Materials and Production, Aalborg University, Fibigerstrede 16, DK 9220 Aalborg, Denmark. ORCID
  2. Izabela Nielsen: Department of Materials and Production, Aalborg University, Fibigerstrede 16, DK 9220 Aalborg, Denmark.
  3. Subrata Saha: Department of Materials and Production, Aalborg University, Fibigerstrede 16, DK 9220 Aalborg, Denmark. ORCID

Abstract

Efficient human resource deployment is one of the key aspects of road traffic management for maintaining the lifelines of any metropolitan city. The problem becomes relevant when collaboration between human resources with different skills in day-to-day operations is necessary to maintain public and commercial transport, manage various social events and emergency situations, and hence reduce congestion, injuries, emissions, etc. This study proposes a two-phase fuzzy multi-objective binary programming model for optimal allocation of five different categories of human resources to minimize the overall operational cost, maximize the allocation to accident-prone road segments, minimize the number of volunteer personnel and maximize the direct contact to reduce emissions and road traffic violations, simultaneously. A binary programming model is formulated to provide an efficient individual manpower allocation schedule for multiple road segments at different shifts. A case study is proposed for model evaluation and to derive managerial implications. The proposed model can be used to draw insights into human resource allocation planning in traffic management to reduce road traffic congestion, injuries and vehicular emissions.

Keywords

References

  1. PLoS One. 2015 Jul 30;10(7):e0131962 [PMID: 26226109]
  2. Traffic Inj Prev. 2012;13 Suppl 1:57-63 [PMID: 22414129]
  3. Accid Anal Prev. 2018 Jun;115:11-24 [PMID: 29529397]
  4. Bull World Health Organ. 2005 Apr;83(4):294-300 [PMID: 15868021]
  5. Trop Anim Health Prod. 2020 Mar;52(2):839-849 [PMID: 31586318]
  6. Lancet. 2015 Jan 10;385(9963):117-71 [PMID: 25530442]
  7. Public Health. 2017 Mar;144S:S39-S44 [PMID: 28288730]
  8. Int J Inj Contr Saf Promot. 2016;23(1):64-71 [PMID: 25109622]

MeSH Term

Accidents, Traffic
Cities
Humans
Models, Theoretical
Resource Allocation
Vehicle Emissions
Workforce

Chemicals

Vehicle Emissions

Word Cloud

Created with Highcharts 10.0.0roadallocationhumantrafficmodeldifferentreduceemissionsbinaryprogrammingresourcemanagementresourcescongestioninjuriesstudyminimizemaximizesegmentsmanpowerproposedEfficientdeploymentonekeyaspectsmaintaininglifelinesmetropolitancityproblembecomesrelevantcollaborationskillsday-to-dayoperationsnecessarymaintainpubliccommercialtransportmanagevarioussocialeventsemergencysituationshenceetcproposestwo-phasefuzzymulti-objectiveoptimalfivecategoriesoveralloperationalcostaccident-pronenumbervolunteerpersonneldirectcontactviolationssimultaneouslyformulatedprovideefficientindividualschedulemultipleshiftscaseevaluationderivemanagerialimplicationscanuseddrawinsightsplanningvehicularMulti-ObjectiveHumanResourceAllocationApproachSustainableTrafficManagementemissioncontrolfuzzy-efficientsolution

Similar Articles

Cited By