The Dial-a-Ride Problem with Synchronized Visits
Boshuai Zhao, Jakob Puchinger, and Roel Leus

TL;DR
This paper introduces a novel Dial-a-Ride Problem variant with synchronized visits for drone fleets, proposing multiple formulations and a dynamic discretization algorithm to optimize routing and scheduling under varying request intensities.
Contribution
It presents four new formulations for the problem and introduces the DDD algorithm, improving solution quality and computational efficiency, especially at high request intensities.
Findings
Event-based formulation performs best at low request intensity.
TSFrag with DDD outperforms other formulations at high request intensity.
Using DDD reduces computation time and iterations.
Abstract
The limited capacity of drones and future one- or two-seat modular vehicles requires multiple units to serve a single large customer (i.e., a customer whose demand exceeds a single vehicle's capacity) simultaneously, whereas small customers (i.e., those whose demand can be served by a single vehicle) can be consolidated in one trip. This motivates the Dial-a-Ride Problem with Synchronized Visits, where a fleet of drones must be routed and scheduled to transport orders at minimum cost. We propose four formulations: arc-based, event-based, time-space event-based (TSEF), and time-space fragment-based (TSFrag). An event is defined as a tuple of a location and a set of onboard customers, while a fragment represents a partial path. For TSEF and TSFrag, we also employ the dynamic discretization discovery (DDD) algorithm, which iteratively refines an initial low-resolution time-space network to…
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Taxonomy
TopicsUAV Applications and Optimization · Vehicle Routing Optimization Methods · Transportation and Mobility Innovations
