Scheduling methodology to minimize random customer arrival

dc.contributor.authorKothalawala, KDHA
dc.contributor.authorSamarasekera, NA
dc.date.accessioned2018-09-20T00:24:06Z
dc.date.available2018-09-20T00:24:06Z
dc.description.abstractThe main problem addressed by the research is random arrival of customers to pick goods at a product distribution center. Using a Case Study approach, a methodology is developed for scheduling of customer arrivals as a solution. Initially the problem is studied in detail. A survey was carried out to study the current customer behavior of the selected product distribution center. Using the findings of the survey and the literature review, different scheduling solutions are generated. Three most viable solutions are selected and then those three solutions are evaluated in financial, operational and change management aspects to find the best solution. A simulation is also done for customer arrivals to quantify the impact of implementing the scheduling system. The findings of the research clearly indicate the feasibility and the customer service improvements derived by customer scheduling. The customer waiting times and the idling of the distribution point assets can be significantly reduced by the developed scheduling system. Customers’ perception of the waiting time can be reduced by providing waiting information of customers prior to their arrival.en_US
dc.identifier.conferenceMoratuwa Engineering Research Conference - MERCon 2015en_US
dc.identifier.departmentDepartment of Transport and Logistics Managementen_US
dc.identifier.emailheshanko777@gmail.comen_US
dc.identifier.emailnsmrskr@yahoo.comen_US
dc.identifier.facultyEngineeringen_US
dc.identifier.placeMoratuwa, Sri Lankaen_US
dc.identifier.urihttp://dl.lib.mrt.ac.lk/handle/123/13579
dc.identifier.year2015en_US
dc.language.isoenen_US
dc.subjectrandom customer arrival; scheduling; customer service improvement, process mapping; distribution; logisticsen_US
dc.titleScheduling methodology to minimize random customer arrivalen_US
dc.typeConference-Abstracten_US

Files

Collections