Integrated Vehicle Routing and Monte Carlo Scheduling Approach for the Home Service Assignment, Routing, and Scheduling Problem

TL;DR

This paper addresses the complex H-SARA problem in home services, integrating vehicle routing and Monte Carlo scheduling under uncertainty, and introduces a novel metaheuristic for solution improvement.

Contribution

It formulates the stochastic H-SARA problem, proposes a two-stage solution approach, and introduces the Route Fracture Metaheuristic for enhanced routing and scheduling.

Findings

The approach effectively manages stochastic travel times and cancellations.

The Route Fracture Metaheuristic improves solution quality.

Insights into optimal routing and scheduling under uncertainty.

Abstract

We formulate and solve the H-SARA Problem, a Vehicle Routing and Appointment Scheduling Problem motivated by home services management. We assume that travel times, service durations, and customer cancellations are stochastic. We use a two-stage process that first generates teams and routes using a VRP Solver with optional extensions and then uses an MC Scheduler that determines expected arrival times by teams at customers. We further introduce two different models of cancellation and their associated impacts on routing and scheduling. Finally, we introduce the Route Fracture Metaheuristic that iteratively improves an H-SARA solution by replacing the worst-performing teams. We present insights into the problem and a series of numerical experiments that illustrate properties of the optimal routing, scheduling, and the impact of the Route Fracture Metaheuristic for both models of cancellation.