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 …

RIME A physics based optimization algorithm, Neurocomputing, 2023 https://doi.org/10.1016/j.neucom.2023.02.010, This paper proposes an efficient optimization algorithm based on the physical phenomenon of rime-ice

Tight multi robot coordination for a multi agent system where the communication range is constrained and the agents need to coordinate and reach there goal destination without violating the range barrier in an obstacle environment.

The optimization field suffers from the metaphor-based “pseudo-novel” or “fancy” optimizers. Most of these cliché methods mimic animals' searching trends and possess a small contribution to the optimization process itself. Most of these cliché methods suffer from the locally efficient performance, biased verification methods on easy problems, an…

Heterogeneous Improved Dynamic Multi-Swarm PSO (HIDMS-PSO) algorithm. Source code for the paper: IEEE SSCI https://ieeexplore.ieee.org/document/9308313

Visit: https://aliasgharheidari.com/HGS.html. HGS optimizer is a population-based method with stochastic switching elements that enrich its main exploratory and exploitative behaviors and flexibility of HGS in dealing with challenging problem landscapes. The algorithm has been compared to LSHADE, SPS_L_SHADE_EIG, LSHADE_cnEpSi, SHADE, SADE, MPED…

The source codes of this algorithm are also publicly available at https://aliasgharheidari.com/INFO.html. This study presents the analysis and principle of an innovative optimizer named weIghted meaN oF vectOrs (INFO) to optimize different problems.

A new optimization method based on the dynamic of sliding motion along a frictionless inclined plane. In IPO, a collection of agents cooperate with each other and move toward better positions in the search space by employing Newton’s second law and equations of motion. The standard version of the IPO is presented by Mozafari et al. in 2016. Powe…

An improvement in convergence rate in the Particle Swarm Optimization Algorithm. The code is written in Matlab. This was my B.Sc. final year project.

With the aim of create a powerful trade-off between the concepts of exploitation and exploration, and rectify the complexity of their structural parameters in the standard IPO, a modified version of IPO (called MIPO) is introduced as an efficient optimization algorithm for digital infinite-impulse-response (IIR) filters model identification. The…

Gravitational Search Algorithm Implementation

Imperialist Competitive Algorithm Implementation

Polar Lights Optimizer (PLO) introduces unique strategies based on the aurora phenomenon, using gyration motion for local exploitation and aurora oval walk for global exploration.

MNSWOA: A nondominated-sorting-based whale optimization algorithm for feature selection.

Moss Growth Optimization (MGO) mimics the natural growth processes of moss to achieve effective optimization through a combination of local and global search strategies

Particle Swarm Optimization Implementation

A Cooperative Optimization method that combines Differential Evolution, Univariate Sampling, Harmony Search and Particle Swarm Optimizer to deal with the 100-Digit Challenge of finding global optimum of multi-modal problems.

A grey wolf optimizer‑based chaotic gravitational search algorithm for global optimization (GWCGSA)

Ant Colony Optimization for Continuous Domains (ACOR) in MATLAB

Escape Algorithm (ESC) models crowd evacuation behaviors to achieve effective optimization through a balance of exploration and exploitation strategies