marinepredator0.0.1 package

Marine Predators Algorithm

F01

Sphere Function (F01)

F02

Sum of Absolute Values and Products (F02)

F03

Sum of Squared Cumulative Sums (F03)

F04

Maximum Absolute Value (F04)

F05

Rosenbrock Function (F05)

F06

Step Function / Shifted Sphere (F06)

F07

Quartic Function with Noise (F07)

F08

Schwefel Function (F08)

F09

Rastrigin Function (F09)

F10

Ackley Function (F10)

F11

Griewank Function (F11)

F12

Penalized Function 1 (F12)

F13

Penalized Function 2 (F13)

F14

Shekel's Foxholes Function (F14)

F15

Kowalik Function (F15)

F16

Six-Hump Camel Back Function (F16)

F17

Branin Function (F17)

F18

Goldstein-Price Function (F18)

F19

Hartmann 3D Function (F19)

F20

Hartmann 6D Function (F20)

F21

Shekel 5 Function (F21)

F22

Shekel 7 Function (F22)

F23

Shekel 10 Function (F23)

get_function_details

Get Function Details

initialize_population

Initialize Population

levy

Levy Flight Random Step Generator

marinepredator-package

mpa: Marine Predators Algorithm

mpa

Marine Predators Algorithm (MPA)

print.mpa_result

Print method for MPA results

test-functions

Test Functions for Optimization

Ufun

Penalty Function for Penalized Test Functions

Download source packageRead PDF manual

Implementation of the Marine Predators Algorithm (MPA) in R. MPA is a nature-inspired optimization algorithm that follows the rules governing optimal foraging strategy and encounter rate policy between predator and prey in marine ecosystems. Based on the paper by Faramarzi et al. (2020) <doi:10.1016/j.eswa.2020.113377>.

  • Maintainer: Marc Grossouvre
  • License: MIT + file LICENSE
  • Last published: 2026-02-04

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