A Novel Algorithm for Solving the Prize Collecting Traveling Salesman Problem Based on DNA Computing

IF 3.7 4区生物学 Q1 BIOCHEMICAL RESEARCH METHODS IEEE Transactions on NanoBioscience Pub Date : 2023-08-22 DOI:10.1109/TNB.2023.3307458

Zhao-Cai Wang;Kun Liang;Xiao-Guang Bao;Tun-Hua Wu

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Abstract

DNA computing is a new pattern of computing that combines biotechnology and information technology. As a new technology born in less than three decades, it has developed at an extremely rapid rate, which can be attributed to its advantages, including high parallelism, powerful data storage capacity, and low power consumption. Nowadays, DNA computing has become one of the most popular research fields worldwide and has been effective in solving certain combinatorial optimization problems. In this study, we use the Adleman-Lipton model based on DNA computing for solving the Prize Collecting Traveling Salesman Problem (PCTSP) and demonstrate the feasibility of this model. Then, we design a simulation experiment of the model to solve some open instances of PCTSP. The results illustrate that the model can satisfactorily solve these instances. Finally, the comparison with the results of the Clustering Search algorithm and the Greedy Stochastic Adaptive Search Procedure/Variable Neighborhood Search method reveals that the optimal solutions obtained by this simulation experiment are significantly superior to those of the other two algorithms in all instances. This research also provides a method for proficiently solving additional combinatorial optimization problems.

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基于DNA计算的解决领奖旅行推销员问题的新算法。

DNA 计算是生物技术与信息技术相结合的一种新型计算模式。作为一项诞生不到三十年的新技术，它的发展速度极为迅猛，这得益于它具有高并行性、强大的数据存储能力和低功耗等优势。如今，DNA 计算已成为全球最热门的研究领域之一，并在解决某些组合优化问题方面卓有成效。在本研究中，我们使用基于 DNA 计算的 Adleman-Lipton 模型来解决有奖旅行推销员问题（PCTSP），并证明了该模型的可行性。然后，我们设计了该模型的仿真实验，以解决 PCTSP 的一些开放实例。结果表明，该模型能令人满意地解决这些实例。最后，通过与聚类搜索算法和贪婪随机自适应搜索程序/可变邻域搜索法的结果进行比较，发现该仿真实验所获得的最优解在所有实例中都明显优于其他两种算法。这项研究还为熟练解决其他组合优化问题提供了一种方法。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

IEEE Transactions on NanoBioscience 工程技术-纳米科技

CiteScore

7.00

自引率

5.10%

发文量

197

审稿时长

>12 weeks

期刊介绍： The IEEE Transactions on NanoBioscience reports on original, innovative and interdisciplinary work on all aspects of molecular systems, cellular systems, and tissues (including molecular electronics). Topics covered in the journal focus on a broad spectrum of aspects, both on foundations and on applications. Specifically, methods and techniques, experimental aspects, design and implementation, instrumentation and laboratory equipment, clinical aspects, hardware and software data acquisition and analysis and computer based modelling are covered (based on traditional or high performance computing - parallel computers or computer networks).

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