Fast Heuristics for the 3-D Multi-Goal Path Planning Based on the Generalized Traveling Salesman Problem With Neighborhoods

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F19%3A00331123" target="_blank" >RIV/68407700:21230/19:00331123 - isvavai.cz</a>

Result on the web

<a href="https://doi.org/10.1109/LRA.2019.2900507" target="_blank" >https://doi.org/10.1109/LRA.2019.2900507</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/LRA.2019.2900507" target="_blank" >10.1109/LRA.2019.2900507</a>

Result language

angličtina

Original language name

Fast Heuristics for the 3-D Multi-Goal Path Planning Based on the Generalized Traveling Salesman Problem With Neighborhoods

Original language description

In this letter, we address the multi-goal path planning problem to determine a cost-efficient path to visit a set of three-dimensional regions. The problem is a variant of the traveling salesman problem with neighborhoods (TSPN) where an individual neighborhood consists of multiple regions, and the problem is to determine a shortest multi-goal path to visit at least one region of each neighborhood. Because each neighborhood may consist of several regions, it forms a neighborhood set, and the problem is called the generalized TSPN (GTSPN) in the literature. We propose two heuristic algorithms to provide a feasible solution of the GTSPN quickly. The first algorithm is based on a decoupled approach using a solution of the generalized TSP that is further improved by a quick post-processing procedure. Besides, we propose to employ the existing unsupervised learning technique called the growing self-organizing array to quickly find a feasible solution of the GTSPN that can be further improved by more demanding optimization. The reported results on existing benchmarks for the GTSPN indicate that both proposed heuristics provide better or competitive solutions than the state-of-the-art reference algorithm, but they are up to two orders of magnitude faster.

Czech name

—

Czech description

—

Type

J_SC - Article in a specialist periodical, which is included in the SCOPUS database

CEP classification

—

OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

Result was created during the realization of more than one project. More information in the Projects tab.

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2019

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

IEEE Robotics and Automation Letters

ISSN

2377-3766

e-ISSN

2377-3766

Volume of the periodical

4

Issue of the periodical within the volume

3

Country of publishing house

US - UNITED STATES

Number of pages

8

Pages from-to

2439-2446

UT code for WoS article

000463616000003

EID of the result in the Scopus database

2-s2.0-85064090682