In:
Mathematics, MDPI AG, Vol. 10, No. 18 ( 2022-09-07), p. 3249-
Abstract:
The traveling salesman problem (TSP) widely exists in real-life practical applications; it is a topic that is under investigation and presents unsolved challenges. The existing solutions still have some challenges in convergence speed, iteration time, and avoiding local optimization. In this work, a new method is introduced, called the discrete carnivorous plant algorithm (DCPA) with similarity elimination to tackle the TSP. In this approach, we use a combination of six steps: first, the algorithm redefines subtraction, multiplication, and addition operations, which aims to ensure that it can switch from continuous space to discrete space without losing information; second, a simple sorting grouping method is proposed to reduce the chance of being trapped in a local optimum; third, the similarity-eliminating operation is added, which helps to maintain population diversity; fourth, an adaptive attraction probability is proposed to balance exploration and the exploitation ability; fifth, an iterative local search (ILS) strategy is employed, which is beneficial to increase the searching precision; finally, to evaluate its performance, DCPA is compared with nine algorithms. The results demonstrate that DCPA is significantly better in terms of accuracy, average optimal solution error, and iteration time.
Type of Medium:
Online Resource
ISSN:
2227-7390
DOI:
10.3390/math10183249
Language:
English
Publisher:
MDPI AG
Publication Date:
2022
detail.hit.zdb_id:
2704244-3
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