TDRP-SA Instances

Published: 15 September 2021| Version 1 | DOI: 10.17632/cxc6p5x4ts.1
Contributor:
Hongqi LI

Description

We formally define the truck and drone routing problem with synchronization on arcs (TDRP-SA). Along truck routes, the locations where trucks can dispatch or retrieve drones, may be any nodes on arcs in the truck routes. At a location for a moving truck dispatching or retrieving drones, the arrival time of the truck, and the departure or arrival time of the drones affect each other, which is addressed here through the synchronization on arcs. An LRL (drone launch/retrieval location) that can be located at any node on arcs traveled by trucks, consists of a truck that keeps traveling on arcs. Each customer should be served exactly once. Customers are classified into two types; the first one is called the truck–drone customer (denoted as the TDC) and the other is called the drone customer (denoted as the DRC). Each truck–drone combination includes one truck carrying a predetermined number of drones. 1. Small-scale instances The depot in the VRPTW instance C101 is used as the depot of the TDRP-SA small-scale instance. Let nc denote the number of customer included. The nc customers are classified into TDCs and DRCs. Each truck carries two drones. The drone and truck capacity are 5 kg and 1000 kg, respectively. The maximum working time of each truck is 10 h, and the maximum flying time of one departure of each drone is 0.67 h. The average velocity of each truck and that of each drone are 60 km/h and 65 km/h, respectively. The variable cost of each truck is 0.8 Chinese Yuan/km, and the operating cost per departure of each drone is 15 Chinese Yuan. The penalty of a truck waiting for a unit of time at customer locations is estimated as 1. Each small-scale instance is denoted by C“nc”-1, C“nc”-2, or C“nc”-3. 2. Large-scale benchmark instances We modify the benchmark instances C101–C109, R101–R112, and RC101–RC108 by classifying customers into TDCs and DRCs. Each of the VRPTW benchmark instances is converted into three types of TDRP-SA test instances using a method of classifying the customers. We modify time windows of the benchmark instances C101–C109 with classified customers. If the model constraints cannot be ensured because of the modified time windows of some customers, the center of the time windows of these customers is adjusted as the arrival time of a vehicle that departs at the depot opening time. The drone and truck capacity are 60 and 1000, respectively. The maximum working time of each truck is 1000, and the maximum flying time of one takeoff for each drone is 40. The average velocity of each truck and that of each drone are 1 and 1.1, respectively. The variable cost of each truck is 1, and the operating cost per departure of each drone is 5. Each large-scale benchmark instance is denoted by “name of VRPTW benchmark instance”-1, “name of VRPTW benchmark instance”-2, or “name of VRPTW benchmark instance”-3.

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Institutions

Beihang University

Categories

Vehicle Routing Problem

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