This article presents a new algorithm which is a modified version of the elite ant system (EAS) algorithm. The new version utilizes an effective criterion for escaping from the local optimum points. In contrast to the classical EAC algorithms, the proposed algorithm uses only a global updating, which will increase pheromone on the edges of the best (i.e. the shortest) route and will at the same time decrease the amount of pheromone on the edges of the worst (i.e. the longest) route. In order to assess the efficiency of the new algorithm, some standard traveling salesman problems (TSPs) were studied and their results were compared with classical EAC and other well-known meta-heuristic algorithms. The results indicate that the proposed algorithm has been able to improve the efficiency of the algorithms in all instances and it is competitive with other algorithms.
EB-GLS: An Improved Guided Local Search Based on the Big Valley Structure
City University of Hong Kong（香港城市大学）；University of Essex（埃塞克斯大学）
局部搜索是模因算法中的基本构建块。引导局部搜索（Guided Local Search，GLS）可以提高局部搜索的效率。通过改变引导函数，广义最小二乘引导局部搜索跳出局部最优解，寻找更优解。GLS的关键组成部分是它的惩罚机制，它决定了当搜索陷入局部最优解时选择哪个特征进行惩罚。原始的GLS惩罚机制仅利用每个特征的代价和当前惩罚值。众所周知，许多组合优化问题具有大的谷结构，即，解越好，它越有可能接近全局最优解。本文提出利用大谷结构假设来改进GLS惩罚机制。提出了一种改进的GLS算法-精英偏置GLS（EB-GLS）。EB-GLS记录并维护精英解作为全局最优解的估计，并减少了惩罚该解中的特征的机会。我们已经系统地测试了对称旅行商问题的算法。实验结果表明，EB-GLS明显优于GLS。
Stochastic Runtime Analysis of a Cross Entropy Algorithm for Traveling Salesman Problems
Beijing Institute for Scientific and Engineering Computing（北京科学与工程计算研究院）；Beijing University of Technology（北京工业大学）；Berlin University of Technology（柏林工业大学）
Eyeballing Combinatorial Problems: A Case Study of Using Multimodal Large Language Models to Solve Traveling Salesman Problems
Queensland University of Technology（昆士兰科技大学）；Minia University（明亚大学）；Al-Ahliyya Amman University（安曼阿赫利亚大学）；Arab American University（阿拉伯美国大学）；Columbia University（哥伦比亚大学）
Experience-Guided Reflective Co-Evolution of Prompts and Heuristics for Automatic Algorithm Design
Gaoling School of Artificial Intelligence, Renmin University of China（中国人民大学北京校区人工智能学院）；Department of Data Science, City University of Hong Kong（香港城市大学数据科学系）；School of Information, Renmin University of China（中国人民大学信息学院）；WeChat, Tencent（微信，腾讯）
A glass-box interactive machine learning approach for solving NP-hard problems with the human-in-the-loop
Medical University Graz（格拉茨医科大学）；Vasile Alecsandri University of Bacǎu（瓦西里·亚历山德里巴克乌大学）；Technical University of Cluj-Napoca（克卢日-纳波卡技术大学）；Coventry University（考文垂大学）
