Method parameters
Method parameters are listed and explained here.
Overview of methods and their variants
Avaliable methods and their variants are summarized in the following table.
Method |
Variant |
Supports constraints |
Remark |
---|---|---|---|
Particle Swarm Optimization (PSO) |
‘Vanilla’ |
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‘TVAC’ |
User must provide at least one of the following stopping criteria: optimizer.max_iterations, optimizer.max_evaluations, optimizer.max_elapsed_time. |
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‘Chaotic’ |
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Fireworks Algorithm (FWA) |
‘Vanilla’ |
||
‘Rank’ |
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Squirrel Search Algorithm (SSA) |
‘Vanilla’ |
||
Differential Evolution (DE) |
‘SHADE’ |
||
‘LSHADE’ |
User must provide at least one of the following stopping criteria: optimizer.max_iterations, optimizer.max_evaluations, optimizer.max_elapsed_time. |
||
Bat Algorithm (BA) |
‘Vanilla’ |
||
Electromagnetic Field Optimization (EFO) |
‘Vanilla’ |
Significantly slower than other methods. Does not support parallel evaluation. |
|
Manta Ray Foraging Optimization (MRFO) |
‘Vanilla’ |
User must provide at least one of the following stopping criteria: optimizer.max_iterations, optimizer.max_evaluations, optimizer.max_elapsed_time. |
|
Artificial Bee Colony (ABC) |
‘Vanilla’ |
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‘FullyEmployed’ |
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Grey Wolf Optimizer (GWO) |
‘Vanilla’ |
User must provide at least one of the following stopping criteria: optimizer.max_iterations, optimizer.max_evaluations, optimizer.max_elapsed_time. |
|
Nelder-Mead (NM) |
‘Vanilla’ |
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‘GaoHan’ |
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Multi-Scale Grid Search (MSGS) |
‘Vanilla’ |
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Random Search (RS) |
‘Vanilla’ |
Legend: Default variant, Constraints supported, Constraints not supported
Specific parameters for each of the available methods and their variants are listed and explained below.
Particle Swarm Optimization (PSO)
Variant |
Parameter |
Allowed values |
Range |
Default |
Description |
---|---|---|---|---|---|
all |
swarm_size |
(int) |
[1, -] |
max (10, dimensions) |
Number of PSO particles |
inertia |
(float) |
[0.5, 1.0] |
0.72 |
Inertia weight |
|
‘LDIW’ |
Linearly decreasing inertia weight (from 1.0 to 0.4) |
||||
‘HSIW’ |
Half sinusoidal inertia weight (from 0.5 to 0.75 and back) |
||||
‘anakatabatic’ |
Adaptive inertia weight technique (Družeta and Ivić, 2020) |
||||
‘Vanilla’ |
cognitive_rate |
(float) |
[0.0, 2.0] |
1.0 |
PSO parameter also known as c1 |
social_rate |
(float) |
[0.0, 2.0] |
1.0 |
PSO parameter also known as c2 |
|
akb_model |
‘Languid’, ‘TipsySpider’, ‘FlyingStork’, ‘MessyTie’ |
‘Languid’ |
Secondary parameter when using inertia=’anakatabatic’ |
||
‘TVAC’ |
akb_model |
‘Languid’, ‘RightwardPeaks’, ‘OrigamiSnake’ |
‘Languid’ |
Secondary parameter when using inertia=’anakatabatic’ |
|
‘Chaotic’ |
max_cls_it |
(int) |
[0, -] |
10 |
Maximum number of chaotic local search iterations |
chaotic_elite |
(float) |
[0.0, 1.0] |
0.2 |
Elite part of the swarm, immune to reinitialization |
|
akb_model |
‘Languid’ |
‘Languid’ |
Secondary parameter when using inertia=’anakatabatic’ |
Fireworks Algorithm (FWA)
Variant |
Parameter |
Allowed values |
Range |
Default |
Description |
---|---|---|---|---|---|
all |
n |
(int) |
[1, -] |
dimensions |
Number of fireworks |
m1 |
(int) |
[1, -] |
dimensions / 2 |
Number of explosion sparks |
|
m2 |
(int) |
[1, -] |
dimensions / 2 |
Number of mutation sparks |
Squirrel Search Algorithm (SSA)
Variant |
Parameter |
Allowed values |
Range |
Default |
Description |
---|---|---|---|---|---|
‘Vanilla’ |
pop_size |
(int) |
[1, -] |
max (20, 2 * dimensions) |
Number of SSA squirrels |
ata |
(float) |
[0.0, 1.0] |
0.5 |
Acorn tree attraction |
|
p_pred |
(float) |
[-, -] |
0.1 |
Predator presence probability |
|
c_glide |
(float) |
[-, -] |
1.9 |
Gliding constant |
|
gd_lim |
(list of 2 floats) |
[0.5, 1.11] |
Gliding distance limits (min, max) |
Differential Evolution (DE)
Variant |
Parameter |
Allowed values |
Range |
Default |
Description |
---|---|---|---|---|---|
all |
pop_init |
(int) |
[1, -] |
18 * dimensions |
Initial population size |
f_archive |
(float) |
[0.0, -] |
2.6 |
External archive size factor |
|
hist_size |
(int) |
[1, -] |
6 |
Size of historical memory |
|
p_mutation |
(float) |
[0.0, 1.0] |
0.11 |
Mutation probability |
Bat Algorithm (BA)
Variant |
Parameter |
Allowed values |
Range |
Default |
Description |
---|---|---|---|---|---|
‘Vanilla’ |
pop_size |
(int) |
[1, -] |
max (15, dimensions) |
Number of BA bats |
loudness |
(float) |
[-, -] |
1.0 |
Loudness |
|
pulse_rate |
(float) |
[-, -] |
0.001 |
Pulse rate |
|
alpha |
(float) |
[-, -] |
0.9 |
Alpha |
|
gamma |
(float) |
[-, -] |
0.1 |
Gamma |
|
freq_range |
(list of 2 floats) |
[0, 1] |
Frequency range (min, max) |
Electromagnetic Field Optimization (EFO)
Variant |
Parameter |
Allowed values |
Range |
Default |
Description |
---|---|---|---|---|---|
‘Vanilla’ |
pop_size |
(int) |
[1, -] |
max (50, dimensions) |
EFO population size |
R_rate |
(float) |
[0.1, 0.4] |
0.25 |
Probability of changing one EM of generated particle with a random EM |
|
Ps_rate |
(float) |
[0.1, 0.4] |
0.25 |
Probability of selecting EMs of generated particle from the positive field |
|
P_field |
(float) |
[0.05, 0.1] |
0.075 |
Portion of population which belongs to positive field |
|
N_field |
(float) |
[0.4, 0.5] |
0.45 |
Portion of population which belongs to negative field |
Manta Ray Foraging Optimization (MRFO)
Variant |
Parameter |
Allowed values |
Range |
Default |
Description |
---|---|---|---|---|---|
‘Vanilla’ |
pop_size |
(int) |
[1, -] |
max (10, dimensions) |
Number of MRFO mantas |
f_som |
(float) |
[-, -] |
2.0 |
Somersault factor |
Artificial Bee Colony (ABC)
Variant |
Parameter |
Allowed values |
Range |
Default |
Description |
---|---|---|---|---|---|
all |
pop_size |
(int) |
[2, -] |
max (10, 2 * dimensions) |
Total number of bees |
trial_limit |
(int) |
[1, -] |
pop_size * dimensions / 2 |
Number of times a bee may try to find a better solution before it is reinitialized |
Grey Wolf Optimizer (GWO)
Variant |
Parameter |
Allowed values |
Range |
Default |
Description |
---|---|---|---|---|---|
all |
pop_size |
(int) |
[5, -] |
max (10, dimensions) |
Number of GWO wolves |
Nelder-Mead (NM)
Variant |
Parameter |
Allowed values |
Range |
Default |
Description |
---|---|---|---|---|---|
all |
init_step |
(float) |
[0, 1] |
0.4 |
Relative size of initial polytope |
‘Vanilla’ |
alpha |
(float) |
[0, -] |
1 |
Reflection factor |
gamma |
(float) |
[0, -] |
2 |
Expansion factor |
|
rho |
(float) |
[0, -] |
0.5 |
Contraction factor |
|
sigma |
(float) |
[0, -] |
0.5 |
Reduction factor |
Multi-Scale Grid Search (MSGS)
Variant |
Parameter |
Allowed values |
Range |
Default |
Description |
---|---|---|---|---|---|
‘Vanilla’ |
n |
(int) |
[1, -] |
10 |
Number of grid divisions in each direction (2n divisions per dimension) |
xtol |
(float) |
[0.0, -] |
1e-6 |
Relative grid size tolerance, i.e. minimum relative grid size as fraction of (ub - lb) |
Random Search (RS)
Variant |
Parameter |
Allowed values |
Range |
Default |
Description |
---|---|---|---|---|---|
‘Vanilla’ |
batch_size |
(int) |
[1, -] |
dimensions |
Number of evaluations per iteration |