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Types & classes27 in github.com/SioKCronin/nature-inspired-optimisation

↓ 7 callersClassIndividual
Represents an individual in the population space.
nio/cultural.py:30
↓ 5 callersClassCulturalAlgorithm
Implementation of the Cultural Algorithm metaheuristic.
nio/cultural.py:63
↓ 4 callersClassCAVisualizer
Visualizer for Cultural Algorithm optimization process.
nio/visualize_ca.py:31
↓ 4 callersClassIWDCO
Intelligent Water Drops algorithm for Continuous Optimization. Enhanced with multiple liquid and soil types, each affecting behavior differen
nio/iwd_co.py:134
↓ 3 callersClassPPSO
Proactive Particle Swarm Optimization algorithm.
nio/ppso.py:40
↓ 3 callersClassWaterCycleAlgorithm
Water Cycle Algorithm for continuous optimization. Enhanced with multiple liquid types, each affecting flow and evaporation behavior.
nio/water_cycle.py:101
↓ 2 callersClassBat
nio/bat.py:25
↓ 2 callersClassBatAlgorithm
Simple yet expressive implementation of the Bat Algorithm.
nio/bat.py:34
↓ 2 callersClassEagle
Represents an eagle in the population.
nio/philippine_eagle.py:40
↓ 2 callersClassFirefly
Represents a firefly in the Firefly Algorithm.
nio/firefly.py:28
↓ 2 callersClassParticle
Represents a particle in PPSO.
nio/ppso.py:29
↓ 2 callersClassWaterBody
Represents a water body (stream, river, or sea) in the WCA.
nio/water_cycle.py:94
↓ 2 callersClassWaterDrop
Represents a water drop in the IWD-CO algorithm.
nio/iwd_co.py:125
↓ 1 callersClassBeliefSpace
Belief space containing cultural knowledge.
nio/cultural.py:57
↓ 1 callersClassCAState
Records state of Cultural Algorithm at a point in time.
nio/visualize_ca.py:569
↓ 1 callersClassContractingOptimum
Dynamic benchmark where the optimum region contracts and moves as optimization progresses. As agents explore the search space and approa
nio/benchmarks.py:28
↓ 1 callersClassDragonfly
nio/dragonfly.py:27
↓ 1 callersClassDragonflyAlgorithm
Dragonfly optimizer with prey interception-aware target planning.
nio/dragonfly.py:33
↓ 1 callersClassFireflyAlgorithm
Firefly Algorithm for multimodal optimization. The Firefly Algorithm is inspired by the flashing behavior of fireflies. Each firefly
nio/firefly.py:34
↓ 1 callersClassNormativeKnowledge
Normative knowledge component of belief space. Stores acceptable ranges and guidance for each dimension.
nio/cultural.py:37
↓ 1 callersClassPhilippineEagleOptimization
Implementation of the Philippine Eagle Optimization Algorithm.
nio/philippine_eagle.py:48
↓ 1 callersClassSituationalKnowledge
Situational knowledge component of belief space. Stores best examples/individuals found so far.
nio/cultural.py:48
ClassLiquidType
Types of liquids with different physical properties.
nio/iwd_co.py:36
ClassLiquidType
Types of liquids with different properties affecting water cycle behavior.
nio/water_cycle.py:37
ClassOperator
Optimization operators.
nio/philippine_eagle.py:31
ClassPhase
Optimization phases.
nio/philippine_eagle.py:25
ClassSoilType
Types of soil with different properties affecting interaction with liquids.
nio/iwd_co.py:80