2026-08-14T17:27:25Z https://drops.dagstuhl.de/oai

oai:drops-oai.dagstuhl.de:14873 2024-03-06T10:31:34Z ddc:004 open_access

Solving the Home Service Assignment, Routing, and Appointment Scheduling (H-SARA) Problem with Uncertainties Johnn, Syu-Ning Zhu, Yiran Miniguano-Trujillo, Andrés Gupte, Akshay Home Health Care Mixed-Integer Linear Programming Two-stage Stochastic Uncertainties A Priori Optimisation Adaptive Large Neighbourhood Search Monte-Carlo Simulation 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. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Syu-Ning Johnn and Yiran Zhu and Andrés Miniguano-Trujillo and Akshay Gupte 2021 Is Part Of OASIcs, Volume 96, 21st Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2021) InProceedings Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/OASIcs.ATMOS.2021.4 urn:nbn:de:0030-drops-148737 https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.ATMOS.2021.4 eng https://creativecommons.org/licenses/by/4.0/legalcode