Parallel DNA Algorithms of Generalized Traveling Salesman Problem-Based Bioinspired Computing Model

- DOI
- 10.2991/ijcis.d.201127.001How to use a DOI?
- Keywords
- DNA computing; Adleman–Lipton model; Generalized traveling salesman problem; NP-hard problem
- Abstract
Generalized traveling salesman problem (GTSP) is a classical combinatorial optimization problem, in which the optimization goal is the minimum route combination. Since the GTSP is a more complex problem than the traveling salesman problem (TSP), the GTSP can be considered an extension of the TSP. At present, compared with TSP, GTSP has been widely used in practice. In GTSP, nodes are divided into clusters, and the problem is divided into two categories according to different constraints. According to the second kind of the GTSP, we propose a parallel biochemical algorithm to solve it. We use deoxyribonucleic acid (DNA) biological strands to represent different vertices, point groups and weights, and get the optimal solutions to a series of different biochemical reaction combinations of DNA sequences. Compared with other algorithms, our algorithm reduces the time complexity to , and proves the feasibility.
- Copyright
- © 2021 The Authors. Published by Atlantis Press B.V.
- Open Access
- This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).
Download article (PDF)
View full text (HTML)
Cite this article
TY - JOUR AU - Xiaomin Ren AU - Xiaoming Wang AU - Zhaocai Wang AU - Tunhua Wu PY - 2020 DA - 2020/12/03 TI - Parallel DNA Algorithms of Generalized Traveling Salesman Problem-Based Bioinspired Computing Model JO - International Journal of Computational Intelligence Systems SP - 228 EP - 237 VL - 14 IS - 1 SN - 1875-6883 UR - https://doi.org/10.2991/ijcis.d.201127.001 DO - 10.2991/ijcis.d.201127.001 ID - Ren2020 ER -