Snail Homing and Mating Search Algorithm: A Novel Bio-Inspired Metaheuristic Algorithm

TL;DR

This paper introduces the Snail Homing and Mating Search (SHMS) algorithm, a new bio-inspired metaheuristic based on snail behavior, demonstrating superior robustness and efficiency in solving optimization problems.

Contribution

The paper presents a novel bio-inspired metaheuristic algorithm, SHMS, inspired by snail behavior, with validated effectiveness in various optimization tasks and real-world engineering applications.

Findings

SHMS outperforms other metaheuristics in robustness and exploration.

SHMS achieves comparable or better solutions with less computational cost.

Successful application to engineering design problems.

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 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.