Snail Homing and Mating Search algorithm: a novel bio-inspired metaheuristic algorithm

Abstract

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 travel 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 solutions obtained from the SHMS algorithm exhibited superior robustness as well as search space exploration capabilities with less computational cost. The real-world application of the SHMS algorithm is successfully demonstrated in the engineering design domain by solving three cases of design and economic optimization Shell and Tube Heat Exchanger (STHE) problem. The objective function value and other statistical results obtained using SHMS algorithm are compared with other well-known metaheuristic algorithms. For Solving STHE Case 1 the SHMS algorithm achieved 0.5–35% minimization of the total cost. For Case 2, 0.6–29% minimization of the total cost has been attained. Furthermore, for Case 3, 0.3%, 0.4% and 52% minimization of total cost is achieved when compared with the ARGA & CI, GA, and original study, respectively. The analysis regarding the convergence of the SHMS algorithm is discussed in detail. The contributions in this paper have opened up several avenues for further applicability of the algorithm for solving complex real-world problems.