Slime Mould Algorithm: A New Method for Stochastic Optimization

In this paper, a new stochastic optimizer, which is called slime mould algorithm (SMA), is proposed based upon the oscillation mode of slime mould in nature. The proposed SMA has several new features with a unique mathematical model that uses adaptive weights to simulate the process of producing positive and negative feedback of the propagation wave of slime mould based on bio-oscillator to form the optimal path for connecting food with excellent exploratory ability and exploitation propensity. The proposed SMA is compared with up-to-date metaheuristics in an extensive set of benchmarks to verify the efficiency. Moreover, four classical engineering structure problems are utilized to estimate the efficacy of the algorithm in optimizing engineering problems. The results demonstrate that the proposed SMA algorithm benefits from competitive, often outstanding performance on different search landscapes. Source codes of SMA are publicly available at http://www.alimirjalili.com/SMA.html

Reference

[1] Shimin Li, Huiling Chen, Mingjing Wang, Ali Asghar Heidari, Seyedali Mirjalili, Slime mould algorithm: A new method for stochastic optimization, Future Generation Computer Systems, 2020. DOI: https://doi.org/10.1016/j.future.2020.03.055