蜗牛归巢与交配搜索算法：一种新型生物启发式元启发式算法
Snail Homing and Mating Search Algorithm: A Novel Bio-Inspired Metaheuristic Algorithm
AI总结：
受蜗牛生物行为启发提出新型元启发式SHMS算法，经多类函数测试与统计检验验证其鲁棒性与探索能力更优、计算成本更低，且在管壳式换热器优化工程问题中表现优于知名同类算法。
摘要：
本文提出了一种新型的蜗牛归巢与交配搜索（Snail Homing and Mating Search, SHMS）算法，其灵感来源于蜗牛的生物行为。蜗牛会持续移动以寻找食物和配偶，沿途留下黏液痕迹作为返程指引，且倾向于跟随地面上的现有痕迹行进，并对附近庇护巢穴发出的信号做出反应。研究通过求解多个单峰函数和多峰函数对所提SHMS算法进行了验证，并采用双侧成对符号秩Wilcoxon检验、Friedman秩检验等标准统计检验对求解结果进行校验。结果表明，SHMS算法所得解具备更优的鲁棒性与搜索空间探索能力，且计算成本更低。研究还通过求解3例管壳式换热器的设计与经济优化问题，成功验证了SHMS算法在工程设计领域的实际应用价值，并将该算法得到的目标函数值及其他统计结果与其他知名元启发式算法进行了对比。
英文摘要：
In this paper, a novel Snail Homing and Mating Search (SHMS) algorithm is proposed. It is inspired from the biological behaviour of the snails. Snails continuously travels to find food and a mate, leaving behind a trail of mucus that serves as a guide for their return. Snails tend to navigate by following the available trails on the ground and responding to cues from nearby shelter homes. The proposed SHMS algorithm is investigated by solving several unimodal and multimodal functions. The solutions are validated using standard statistical tests such as two-sided and pairwise signed rank Wilcoxon test and Friedman rank test. The solution obtained from the SHMS algorithm exhibited superior robustness as well as search space exploration capabilities within the less computational cost. The real-world application of SHMS algorithm is successfully demonstrated in the engineering design domain by solving three cases of design and economic optimization shell and tube heat exchanger problem. The objective function value and other statistical results obtained using SHMS algorithm are compared with other well-known metaheuristic algorithms.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
