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Solving the Home Service Assignment, Routing, and Appointment Scheduling (H-SARA) Problem with Uncertainties

Authors Syu-Ning Johnn , Yiran Zhu , Andrés Miniguano-Trujillo , Akshay Gupte



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Syu-Ning Johnn
  • School of Mathematics, The University of Edinburgh, UK
Yiran Zhu
  • School of Mathematics, The University of Edinburgh, UK
Andrés Miniguano-Trujillo
  • The University of Edinburgh, UK
  • Heriot-Watt University, Edinburgh, UK
  • Maxwell Institute for Mathematical Sciences, Edinburgh, UK
Akshay Gupte
  • School of Mathematics, The University of Edinburgh, UK

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Syu-Ning Johnn, Yiran Zhu, Andrés Miniguano-Trujillo, and Akshay Gupte. Solving the Home Service Assignment, Routing, and Appointment Scheduling (H-SARA) Problem with Uncertainties. In 21st Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2021). Open Access Series in Informatics (OASIcs), Volume 96, pp. 4:1-4:21, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2021)
https://doi.org/10.4230/OASIcs.ATMOS.2021.4

Abstract

The Home Service Assignment, Routing, and Appointment scheduling (H-SARA) problem integrates the strategic fleet-sizing, tactical assignment, operational vehicle routing and scheduling problems at different decision levels, with a single period planning horizon and uncertainty (stochasticity) from the service duration, travel time, and customer cancellation rate. We propose a stochastic mixed-integer linear programming model for the H-SARA problem. Additionally, a reduced deterministic version is introduced which allows to solve small-scale instances to optimality with two acceleration approaches. For larger instances, we develop a tailored two-stage decision support system that provides high-quality and in-time solutions based on information revealed at different stages. Our solution method aims to reduce various costs under stochasticity, to create reasonable routes with balanced workload and team-based customer service zones, and to increase customer satisfaction by introducing a two-stage appointment notification system updated at different time stages before the actual service. Our two-stage heuristic is competitive to CPLEX’s exact solution methods in providing time and cost-effective decisions and can update previously-made decisions based on an increased level of information. Results show that our two-stage heuristic is able to tackle reasonable-size instances and provides good-quality solutions using less time compared to the deterministic and stochastic models on the same set of simulated instances.

Subject Classification

ACM Subject Classification
  • Mathematics of computing → Combinatorial optimization
  • Mathematics of computing → Combinatorial algorithms
  • Applied computing → Transportation
  • Mathematics of computing → Probabilistic algorithms
Keywords
  • Home Health Care
  • Mixed-Integer Linear Programming
  • Two-stage Stochastic
  • Uncertainties A Priori Optimisation
  • Adaptive Large Neighbourhood Search
  • Monte-Carlo Simulation

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