# bahman-ahmadi-aso/dynamic-hunting-leadership-optimization architecture

> Architecture diagram of the GitHub repository bahman-ahmadi-aso/dynamic-hunting-leadership-optimization, generated by GitDiagram from its file tree, README and a sample of source files (last updated 2026-09-25). It is an AI-made overview: check details against the source.

- Interactive diagram: https://gitdiagram.com/bahman-ahmadi-aso/dynamic-hunting-leadership-optimization
- Repository: https://github.com/bahman-ahmadi-aso/dynamic-hunting-leadership-optimization

## Overview

This MATLAB repository implements Dynamic Hunting Leadership (DHL), a family of four metaheuristic optimizers, alongside other optimization algorithms. The documented workflow is to apply an optimizer to benchmark or practical optimization problems and compare solution quality. The tree identifies likely entry, selection, and algorithm modules, but no source excerpts were available, so internal call wiring and the exact role of several files cannot be verified; the graph shows only documented relationships.

Main entry points: [`Select_Functions.m`](https://github.com/bahman-ahmadi-aso/dynamic-hunting-leadership-optimization/blob/main/Select_Functions.m) (Benchmark functions), [`DHLs/DHL_V1.m`](https://github.com/bahman-ahmadi-aso/dynamic-hunting-leadership-optimization/blob/main/DHLs/DHL_V1.m) (DHL variant 1), [`DHLs/DHL_V2.m`](https://github.com/bahman-ahmadi-aso/dynamic-hunting-leadership-optimization/blob/main/DHLs/DHL_V2.m) (DHL variant 2), [`DHLs/DHL_V3.m`](https://github.com/bahman-ahmadi-aso/dynamic-hunting-leadership-optimization/blob/main/DHLs/DHL_V3.m) (DHL variant 3)

## Diagram (Mermaid)

```mermaid
flowchart TD

subgraph group_workflow["Optimization workflow"]
  node_main["Main code<br/>[Main_code.m]"]
  node_selection["Function selection<br/>[Select_Functions.m]"]
  node_benchmarks["Benchmark functions<br/>[Select_Functions.m]"]
  node_applications["Practical problems"]
end

subgraph group_dhl["DHL variants"]
  node_dhlv1["DHL variant 1<br/>[DHL_V1.m]"]
  node_dhlv2["DHL variant 2<br/>[DHL_V2.m]"]
  node_dhlv3["DHL variant 3<br/>[DHL_V3.m]"]
  node_dhlv4["DHL variant 4<br/>[DHL_V4.m]"]
  node_dhlinit["DHL initialization<br/>[initialization.m]"]
  node_boundary["Boundary check<br/>[checkB.m]"]
  node_leaderplot["Leader plotting<br/>[plot_nleader.m]"]
end

subgraph group_algorithms["Other algorithms"]
  node_alternatives["Alternative optimizers"]
  node_gwo["Grey Wolf Optimizer<br/>[GWO.m]"]
  node_mvo["Multi-Verse Optimizer<br/>[MVO.m]"]
  node_pso["Particle Swarm<br/>[PSO.m]"]
  node_levy["Levy operator<br/>[Levy.m]"]
  node_roulette["Roulette selection"]
  node_alginit["Algorithm initialization<br/>[initialization.m]"]
end

node_researcher(("Optimizer user"))

node_researcher -->|"applies"| node_dhlv1
node_researcher -->|"applies"| node_dhlv2
node_researcher -->|"applies"| node_dhlv3
node_researcher -->|"applies"| node_dhlv4
node_dhlv1 -->|"benchmarked on"| node_benchmarks
node_dhlv2 -->|"benchmarked on"| node_benchmarks
node_dhlv3 -->|"benchmarked on"| node_benchmarks
node_dhlv4 -->|"benchmarked on"| node_benchmarks
node_dhlv1 -->|"applied to"| node_applications
node_dhlv2 -->|"applied to"| node_applications
node_dhlv3 -->|"applied to"| node_applications
node_dhlv4 -->|"applied to"| node_applications

click node_main "https://github.com/bahman-ahmadi-aso/dynamic-hunting-leadership-optimization/blob/main/Main_code.m"
click node_selection "https://github.com/bahman-ahmadi-aso/dynamic-hunting-leadership-optimization/blob/main/Select_Functions.m"
click node_benchmarks "https://github.com/bahman-ahmadi-aso/dynamic-hunting-leadership-optimization/blob/main/Select_Functions.m"
click node_dhlv1 "https://github.com/bahman-ahmadi-aso/dynamic-hunting-leadership-optimization/blob/main/DHLs/DHL_V1.m"
click node_dhlv2 "https://github.com/bahman-ahmadi-aso/dynamic-hunting-leadership-optimization/blob/main/DHLs/DHL_V2.m"
click node_dhlv3 "https://github.com/bahman-ahmadi-aso/dynamic-hunting-leadership-optimization/blob/main/DHLs/DHL_V3.m"
click node_dhlv4 "https://github.com/bahman-ahmadi-aso/dynamic-hunting-leadership-optimization/blob/main/DHLs/DHL_V4.m"
click node_dhlinit "https://github.com/bahman-ahmadi-aso/dynamic-hunting-leadership-optimization/blob/main/DHLs/initialization.m"
click node_boundary "https://github.com/bahman-ahmadi-aso/dynamic-hunting-leadership-optimization/blob/main/DHLs/checkB.m"
click node_leaderplot "https://github.com/bahman-ahmadi-aso/dynamic-hunting-leadership-optimization/blob/main/DHLs/plot_nleader.m"
click node_alternatives "https://github.com/bahman-ahmadi-aso/dynamic-hunting-leadership-optimization/blob/main/OptimizationAlgorithms.m"
click node_gwo "https://github.com/bahman-ahmadi-aso/dynamic-hunting-leadership-optimization/blob/main/Algorithms/GWO.m"
click node_mvo "https://github.com/bahman-ahmadi-aso/dynamic-hunting-leadership-optimization/blob/main/Algorithms/MVO.m"
click node_pso "https://github.com/bahman-ahmadi-aso/dynamic-hunting-leadership-optimization/blob/main/Algorithms/PSO.m"
click node_levy "https://github.com/bahman-ahmadi-aso/dynamic-hunting-leadership-optimization/blob/main/Algorithms/Levy.m"
click node_roulette "https://github.com/bahman-ahmadi-aso/dynamic-hunting-leadership-optimization/blob/main/Algorithms/RouletteWheelSelection.m"
click node_alginit "https://github.com/bahman-ahmadi-aso/dynamic-hunting-leadership-optimization/blob/main/Algorithms/initialization.m"

classDef toneNeutral fill:#f8fafc,stroke:#334155,stroke-width:1.5px,color:#0f172a
classDef toneBlue fill:#dbeafe,stroke:#2563eb,stroke-width:1.5px,color:#172554
classDef toneAmber fill:#fef3c7,stroke:#d97706,stroke-width:1.5px,color:#78350f
classDef toneMint fill:#dcfce7,stroke:#16a34a,stroke-width:1.5px,color:#14532d
classDef toneRose fill:#ffe4e6,stroke:#e11d48,stroke-width:1.5px,color:#881337
classDef toneIndigo fill:#e0e7ff,stroke:#4f46e5,stroke-width:1.5px,color:#312e81
classDef toneTeal fill:#ccfbf1,stroke:#0f766e,stroke-width:1.5px,color:#134e4a
class node_main,node_selection,node_benchmarks,node_applications,node_researcher toneBlue
class node_dhlv1,node_dhlv2,node_dhlv3,node_dhlv4,node_dhlinit,node_boundary,node_leaderplot toneAmber
class node_alternatives,node_gwo,node_mvo,node_pso,node_levy,node_roulette,node_alginit toneMint
```

## Components

### Optimization workflow

- [Main code](https://github.com/bahman-ahmadi-aso/dynamic-hunting-leadership-optimization/blob/main/Main_code.m): `Main_code.m`
- [Function selection](https://github.com/bahman-ahmadi-aso/dynamic-hunting-leadership-optimization/blob/main/Select_Functions.m): `Select_Functions.m`
- [Benchmark functions](https://github.com/bahman-ahmadi-aso/dynamic-hunting-leadership-optimization/blob/main/Select_Functions.m): `Select_Functions.m`
- **Practical problems**

### DHL variants

- [DHL variant 1](https://github.com/bahman-ahmadi-aso/dynamic-hunting-leadership-optimization/blob/main/DHLs/DHL_V1.m): `DHLs/DHL_V1.m`
- [DHL variant 2](https://github.com/bahman-ahmadi-aso/dynamic-hunting-leadership-optimization/blob/main/DHLs/DHL_V2.m): `DHLs/DHL_V2.m`
- [DHL variant 3](https://github.com/bahman-ahmadi-aso/dynamic-hunting-leadership-optimization/blob/main/DHLs/DHL_V3.m): `DHLs/DHL_V3.m`
- [DHL variant 4](https://github.com/bahman-ahmadi-aso/dynamic-hunting-leadership-optimization/blob/main/DHLs/DHL_V4.m): `DHLs/DHL_V4.m`
- [DHL initialization](https://github.com/bahman-ahmadi-aso/dynamic-hunting-leadership-optimization/blob/main/DHLs/initialization.m): `DHLs/initialization.m`
- [Boundary check](https://github.com/bahman-ahmadi-aso/dynamic-hunting-leadership-optimization/blob/main/DHLs/checkB.m): `DHLs/checkB.m`
- [Leader plotting](https://github.com/bahman-ahmadi-aso/dynamic-hunting-leadership-optimization/blob/main/DHLs/plot_nleader.m): `DHLs/plot_nleader.m`

### Other algorithms

- [Alternative optimizers](https://github.com/bahman-ahmadi-aso/dynamic-hunting-leadership-optimization/blob/main/OptimizationAlgorithms.m): `OptimizationAlgorithms.m`
- [Grey Wolf Optimizer](https://github.com/bahman-ahmadi-aso/dynamic-hunting-leadership-optimization/blob/main/Algorithms/GWO.m): `Algorithms/GWO.m`
- [Multi-Verse Optimizer](https://github.com/bahman-ahmadi-aso/dynamic-hunting-leadership-optimization/blob/main/Algorithms/MVO.m): `Algorithms/MVO.m`
- [Particle Swarm](https://github.com/bahman-ahmadi-aso/dynamic-hunting-leadership-optimization/blob/main/Algorithms/PSO.m): `Algorithms/PSO.m`
- [Levy operator](https://github.com/bahman-ahmadi-aso/dynamic-hunting-leadership-optimization/blob/main/Algorithms/Levy.m): `Algorithms/Levy.m`
- [Roulette selection](https://github.com/bahman-ahmadi-aso/dynamic-hunting-leadership-optimization/blob/main/Algorithms/RouletteWheelSelection.m): `Algorithms/RouletteWheelSelection.m`
- [Algorithm initialization](https://github.com/bahman-ahmadi-aso/dynamic-hunting-leadership-optimization/blob/main/Algorithms/initialization.m): `Algorithms/initialization.m`

### Other components

- **Optimizer user**

## Connections

- Optimizer user → DHL variant 1: applies
- Optimizer user → DHL variant 2: applies
- Optimizer user → DHL variant 3: applies
- Optimizer user → DHL variant 4: applies
- DHL variant 1 → Benchmark functions: benchmarked on
- DHL variant 2 → Benchmark functions: benchmarked on
- DHL variant 3 → Benchmark functions: benchmarked on
- DHL variant 4 → Benchmark functions: benchmarked on
- DHL variant 1 → Practical problems: applied to
- DHL variant 2 → Practical problems: applied to
- DHL variant 3 → Practical problems: applied to
- DHL variant 4 → Practical problems: applied to