Loughborough University
Leicestershire, UK
LE11 3TU
+44 (0)1509 263171
Loughborough University

Loughborough University Institutional Repository

Please use this identifier to cite or link to this item: https://dspace.lboro.ac.uk/2134/33537

Title: Service scheduling to minimise the risk of missing appointments
Authors: Ji, Chenlu
Liret, Anne
Owusu, Gilbert
Liu, Jiyin
Dorne, Raphael
Rana, Rupal
Keywords: Vehicle routing with time windows
Stochastic service time
Risk minimisation
Issue Date: 2018
Publisher: © IEEE
Citation: JI, C. ...et al., 2018. Service scheduling to minimise the risk of missing appointments. Proceedings of Computing Conference 2017, London, 18-20th. July, pp. 971-980.
Abstract: © 2017 IEEE. This paper introduces the risk minimisation objective in the Stochastic Vehicle Routing Problem (SVRP). In the studied variant of SVRP, technicians drive to customer sites to provide service. The service times and travel times are stochastic, and a time window is required for the start of the service for each customer. Most previous research uses a chance-constrained approach to the problem. Some consider the probability of journey duration exceeding the threshold of the driver's workload while others set restrictions on the probability of individual time window constraints being violated. Their objectives are related to traditional routing costs whilst a different approach was taken in this paper. The risk of missing a task is defined as the probability that the technician assigned to the task arrives at the customer site later than the time window. The problem studied in this paper is to generate a schedule that minimises the maximum risk and sum of risks of the tasks. The duration of each task may be considered as following a known normal distribution. However the distribution of the start time of the service at a customer site will not be normally distributed due to time window constraints. Therefore a multiple integral expression of the risk was derived, and this expression works whether task distribution is normal or not. Additionally a deterministic heuristic searching method was applied to solve the problem. Experiments are carried out to test the method. Results of this work have been applied to an industrial case of SVRP where field engineering individuals drive to customer sites to provide time-constrained services. This original approach allows organisations to pay more attention to increasing customer satisfaction and become more competitive in the market.
Description: Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Version: Accepted for publication
DOI: 10.1109/SAI.2017.8252211
URI: https://dspace.lboro.ac.uk/2134/33537
Publisher Link: https://doi.org/10.1109/SAI.2017.8252211
ISBN: 9781509054435
Appears in Collections:Conference Papers and Presentations (Business)

Files associated with this item:

File Description SizeFormat
Liu_Service Scheduling to Minimise Risk - SAIConference PAPER.pdfAccepted version478.86 kBAdobe PDFView/Open


SFX Query

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.