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add wfg pareto front #114

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gemsanyu
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the pareto front generating methods are previously commented out
also added lexicographical sort so that it can be drawn as line by
pyplot for 2-objective

but the visualization is a bit odd at the right end of the 2-D pareto fronts

@blankjul
NSGA3 Implementation
745ab66
@blankjul
Fixed import error
cf9f33d
@blankjul
Added BestOrderSort and vectorized mating operators
bef1f45
@blankjul
Fixed BestOrderSort
fdea49e
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Removed uncessary files
87cae62
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Archived old operators
8d61bc8
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Changed interface
ad61643
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Termination Criterium Added
7ca98e2
@blankjul
Removed error in optimize.py
fa56895
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MOEAD
1006bf9
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Minor changes
d6a9f6b
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RNSGA3
3bb2989
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RNSGA3 - Cleanup
bef9ea0
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Import error fix
8d8e9be
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UNSGA3 Fix
82e6fa3
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gitlab
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Added gitlab file
7ce01d1
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changed gitlab-ci
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host
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webhook
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Added pseudo weights
36b32ae
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Added reference_direction class
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Import error fix
d778183
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current verison of development - needs to be cleaned
aade895
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new object design
49d70c8
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new test structure and readme.rst change
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gitlab modification
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rename test suite
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VERSION 0.2.1
6f014fb
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VERSION 0.2.2-dev
001809c
Julian Blank and others added 26 commits July 6, 2020 17:48
o
88e1a84
efficient_non_dominated_sort in Cython
a81a900
Loop-wise Algorithm Execution and Checkpoints
518efea
Improved Documentation
392db7c
@cyrilpic
Add wrapper to MODAct problems
55bdf26
Individual as dictionary implementation
ffe5770
Revmoed Templated Individual
6bad624
VERSION 0.4.2
edbb420
Fix == for star
f96b76c
@blankjul
Merge pull request anyoptimization#94 from cyrilpic/modact
2642236 
Add wrapper to MODAct problems
RVEA
478acda
@AvivSham
Update hv.py
dc4a238
@blankjul
Merge pull request anyoptimization#97 from AvivSham/master
3ee6e08 
bug fix in hv.py under vendor
Added GodenSectionSearch, RVEA and GDE3
42a5da6
@hugolmn
Fixed getting started mistake for n_offsprings
ea533ca
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Merge pull request anyoptimization#104 from hugolmn/patch-1
b60c385 
Fixed getting started mistake for n_offsprings
Added usage file showing how to implement an evalution function in ma…
c077e5b 
…tlab
Remove matlab_usage from CI
600629e
@gemsanyu
Added single objective cuckoo search
0596430 
the implementation is based on the Nature Inspired Algorithms Book
and XS Yang CS implementation at
https://www.mathworks.com/matlabcentral/fileexchange/29809-cuckoo-search-cs-algorithm
@gemsanyu
refactor socs
a33f011 
-refactor get global step
-add survival in initialization (for mocs to trigger)
-user termination as given in parameter
-add comment
@gemsanyu
Added Multi Objective Cuckoo Search
5082cc1 
Similar to CS but with multi objective survival from nsga2 or nsga3
@gemsanyu
Fix CS and add pics to docs
917b6d8 
-fix cs use normal distribution instead of uniform in Mantegna's Algorithm
-fix step size scale is now per dimension of x bounds not scalar (alfa)
-add pics to docs
@blankjul
Merge pull request anyoptimization#112 from gemsanyu/add-mocs
71f2db0 
Add Multiple Objective Cuckoo Search
Added scipy wrapper to algorithms
11e745f
Trying to fix usage test
75ad2b2
@gemsanyu
add wfg pareto front
3ca00b1 
the pareto front generating methods are previously commented out
also added lexicographical sort so that it can be drawn as line by
pyplot for 2-objective
@blankjul
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blankjul commented Dec 2, 2020

Thanks for the contribution. Does this generalize to ND too?
(can't remember why I commented it out to be honest)

@gemsanyu
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gemsanyu commented Dec 4, 2020 •
edited

Hey, I just saw your reply. Yes.
I now know why the 2D visualization is off (a "wide" gap between points). It's because of the random generation of the PF. Even if I set the size of the PF to 1000, the gap is still visible. However, I haven't really check its effect on the IGD calculation. What do you think?

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8 participants
@gemsanyu @blankjul @Peng-YM @yashvesikar @JoshKarpel @cyrilpic @AvivSham @hugolmn