Index

List of implemented metaheuristics. The algorithms were implemented based on the contributor's understanding of the algorithms detailed in the published paper.

Quick Selection Guide

By Problem Type

Box-constrained (continuous): Use ECA, DE, PSO, or SHADE
Constrained optimization: Use εDE, ECA, or SHADE
Multi-objective (2-3 objectives): Use NSGA2, SPEA2, or SMS_EMOA
Many-objective (>3 objectives): Use NSGA3
Constrained multi-objective: Use NSGA2, NSGA3, or CCMO
Permutation-based: Use GA with OrderCrossover or BRKGA
Binary: Use GA with BitFlipMutation
Large-scale: Use CSO

Performance Characteristics

Fast convergence: ECA, SHADE
Good for multimodal: DE, PSO, ABC
Robust: NSGA2, ECA
Simple to use: ECA, DE, PSO

Batch Evaluation

Algorithms marked with ✅ in "Batch Evaluation" column support simultaneous evaluation of multiple solutions, which is useful for:

Parallel computing with threads or distributed systems
GPU acceleration
Expensive function evaluations

Set parallel_evaluation=true in Options to enable batch evaluation. See Parallelization tutorial for details.

Algorithm Table

Algorithm	Objective	Constraints	Large Scale	Batch Evaluation	Structure Name
ECA	Single	✅	➖	✅	`ECA`
DE	Single	✅	➖	✅	`DE`
PSO	Single	✅	➖	✅	`PSO`
ABC	Single	❌	➖	❌	`ABC`
MOEA/D-DE	Multi	➖	➖	❌	`MOEAD_DE`
GSA	Single	❌	❌	✅	`CGSA`
SA	Single	✅	➖	❌	`SA`
NSGA-II	Multi	✅	➖	✅	`NSGA2`
NSGA-III	Many	✅	➖	✅	`NSGA3`
SMS-EMOA	Multi	✅	➖	✅	`SMS_EMOA`
SPEA2	Multi	✅	➖	✅	`SPEA2`
BCA	Bilevel	✅	❌	❌	`BCA`
MCCGA	Single	❌	❌	❌	`MCCGA`
GA	Single	✅	➖	✅	`GA`
CCMO	Multi	✅	➖	✅	`CCMO`
$\varepsilon$DE	Single	✅	➖	✅	`εDE`
BRKGA	Single	✅	➖	✅	`BRKGA`
SHADE	Single	✅	➖	✅	`SHADE`
CSO	Single	✅	✅	✅	`CSO`

✅ = supported, ❌ = not supported, ➖ = can be supported by changing default parameters.

Batch Evaluation = Simultaneous evaluation of multiple solutions (batch) see "Batch Evaluation".
Constraints = Equality and inequality constraints.
Large Scale = High dimensional problems (variables space).