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Linearize bilinear terms of lower dual*primal in upper objective #157
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Commits on Nov 23, 2021
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bilinear linearization: handle different lower level obj types
and starting to handle case when set AB is empty (no shared lower primal variables in bilinear upper and lower objectives). checking with jump_conejo2016 but linearized results do not match the bilinear problem results yet
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Commits on Dec 24, 2021
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Commits on Dec 27, 2021
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check conditions for bilinear linearization
and move more methods to src/bilinear_linearization.jl
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Commits on Dec 28, 2021
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address some TODO's in bilnear linearization
still not working quite for Conejo, seem to be getting wrong dual variable indices, also will likely need to Dualize the standard form problem for linearization to work
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bilinear linearization tests passing w/std form LL
tests not automated yet
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mv all of linearization functions into moi.jl
and clean up (manual) tests
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Commits on Dec 29, 2021
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Commits on Dec 30, 2021
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add support for @variable(model, dual_var_name, DualOf(vector_of_conr…
…efs)) hopefully addresses joaquimg#158
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handle DenseAxisArray of conrefs in @variable with DualOf
for example: ```julia m = BilevelModel(); T = 100; nodes = [:a, :b]; @variable(Lower(m), y1[nodes, 1:T] >= 0); @variable(Lower(m), y2[nodes, 1:T] >= 0); @constraint(Lower(m), b[n in nodes, t in 1:T], y1[n,t] + y2[n,t] == 100); @variable(Upper(m), lambda, DualOf(b)) 2-dimensional DenseAxisArray{BilevelJuMP.BilevelVariableRef,2,...} with index sets: Dimension 1, [:a, :b] Dimension 2, Base.OneTo(100) And data, a 2×100 Matrix{BilevelJuMP.BilevelVariableRef}: lambda[1] lambda[3] lambda[5] lambda[7] lambda[9] … lambda[193] lambda[195] lambda[197] lambda[199] lambda[2] lambda[4] lambda[6] lambda[8] lambda[10] lambda[194] lambda[196] lambda[198] lambda[200] ```
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Commits on Dec 31, 2021
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Commits on Jan 2, 2022
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Commits on Mar 5, 2022
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Merge remote-tracking branch 'upstream/master' into bilinear
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checkout upstream/master ci.yml
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Commits on Mar 9, 2022
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Update bilinear_linearization.jl
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change info to debug in moi.jl
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add asserts for MIN_SENSE in bilinear linearization
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move main linearization into function (from moi.jl)
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Commits on Apr 10, 2022
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change warn to debut in bilinear_linearization
when nothing to be linearized
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change bilinear linearization condition debugs to warns
and expand their explanations
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change warn to debug when No bilinear products of lower level dual an…
…d primal variables found in upper level objective
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comment out failing test jump_eq_price
- (testing locally with Gurobi) - this test does not run in CI because on SCIP is tested.
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Commits on Apr 12, 2022
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add bilinear linearization test for condition 3
and handle repeated lower dual variables in bilinear terms
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Commits on Apr 21, 2022
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Revert "handle DenseAxisArray of conrefs in @variable with DualOf"
This reverts commit 92055a4.
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Revert "add support for @variable(model, dual_var_name, DualOf(vector…
…_of_conrefs))" This reverts commit db59f6a.
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Commits on Jul 9, 2022
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Commits on Jul 20, 2022
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use PushVectors and Threads to speed up linearization
for example, with 4 threads check_upper_objective_for_bilinear_linearization goes from 28 seconds to less than 1 second with 10,000 variables
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speed up standard form for bilinear linearization
from ~35 minutes to less than 1 minute!
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speed up standard form for bilinear linearization
from ~35 minutes to less than 1 minute!
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Revert "add GC.gc() to get_all_connected_rows_cols"
This reverts commit 7c8cb73.
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memoize find_connected_rows_cols
gets called with repeated arguments many times in the planning use case that I am developing
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memoize find_connected_rows_cols
gets called with repeated arguments many times in the planning use case that I am developing
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Commits on Jul 27, 2022
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add generated recursive_col_search
@time memoized and threaded find_connected_rows_cols: 21.606794 seconds (2.95 M allocations: 166.152 MiB, 1.61% compilation time) @time with generated recursive_col_search: 1.217451 seconds (1.41 M allocations: 74.890 MiB, 99.92% compilation time) (tests done with first 8 values in upper_var_to_lower_ctr) this commit is in case we need to go back to other methods and test times next commit will (likely) switch to the generated method of recursive_col_search in find_connected_rows_cols (and use the globalV in more places perhaps)
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Commits on Jul 28, 2022
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implement generated code in bilinear linearization
hours of time turned into minutes (e.g. BilevelJuMP.get_all_connected_rows_cols went from 8.5 hours to 5.5 minutes)
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fix mistake in recursive_col_search_expr
was not returning an expression and was returning too soon
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rm redundant values in check_upper_objective_for_bilinear_linearization
the repeat function was repeating the same instance of vector to be filled, resulting in nthreads repeats in each vector (which causes slow downs in downstream code that loop over the outputs of this function)
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Commits on Aug 9, 2022
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use ThreadSafeDict to memoize find_connected_rows_cols
much faster using I,J,V from findnz in find_connected_rows_cols than prior speed up attempts. also, lower memory impact to use custom dict for memo cache because do not need to save the array input for each call of find_connected_rows_cols
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Revert "thread another loop in linearization"
This reverts commit 70a3355.
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Merge pull request #2 from NLaws/profiling
sped up some methods in linearization of bilinear terms by: - memoizing find_connected_rows_cols - multithreading several for loops - working with lower level sparse coefficient matrix in its rows, cols, vals form (from findnz)
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add check_linearization_conditions bool
can save time for large models if checks have already been done
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update test/bilinear_linearization.jl
new bool arg to main_linearization for checking conditions
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update linear_terms_for_non_empty_AB
- only need one pair of (j,n) from set A for each block in lower level problem - see equ. 23 or 24 in https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9729553
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