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update after rh fix#123

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ac/ordc
Jun 24, 2026
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update after rh fix#123
jd-lara merged 1 commit into
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ac/ordc

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@jd-lara jd-lara commented Jun 24, 2026

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@rodrigomha
Add scalar LinearFunctionData unwrap_for_param for time-series cost p…
3a99811 
…arams (#122)

Time-series cost fields (shut_down / no_load and other scalar-linear sides of a
MarketBidTimeSeriesCost) resolve per-hour to an IS.LinearFunctionData. The PWL
slope/breakpoint unwrap_for_param methods don't match it, so it fell through the
identity and _size_wrapper then called size(::LinearFunctionData) (no method),
failing the parameter-population assert. Extract the scalar via get_proportional_term
(mirrors the static _shutdown_cost_value path).
@jd-lara jd-lara merged commit 429c566 into main Jun 24, 2026
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@jd-lara jd-lara deleted the ac/ordc branch June 24, 2026 00:29
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Performance Results
Main

Network: 10 nodes, 13 edges, 3 cost segments
Generators: 5, Demands: 5
Loss coefficients (a, b, c) per generator:
  n1: a=0.007287  b=0.005968  c=0.003850
  n2: a=0.001094  b=0.009002  c=0.007028
  n3: a=0.007897  b=0.008552  c=0.003001
  n4: a=0.008179  b=0.002530  c=0.009637
  n5: a=0.009778  b=0.009934  c=0.009099

Solver logs: /home/runner/work/InfrastructureOptimizationModels.jl/InfrastructureOptimizationModels.jl/main/test/performance/logs/solver_2026-06-24T00-51-10.log

==============================================================================================================================================
Bilinear Approximation Benchmarks
  Refinement = depth for all methods
==============================================================================================================================================
Method          R   Vars Constrs   Bins    Objective   Gap(%) MIPGap(%)     LowerBnd  rmse δbi   max δbi   rmse δq    max δq  build_t  solve_t
----------------------------------------------------------------------------------------------------------------------------------------------
NLP (Ipopt)     -     40     105      0     0.956760        -         -            -  0.00e+00  0.00e+00  0.00e+00  0.00e+00   0.0281   0.0039

NLP (Uno)       -     40     105      0     0.956760   0.0000         -            -  0.00e+00  0.00e+00  0.00e+00  0.00e+00   0.0014   0.0050

Bin2+sSOS       4    190     535      0     1.180700  23.4061    0.0000     1.180700  8.07e-02  1.41e-01  2.49e+01  5.48e+01   0.0062   1.4825
Bin2+sSOS       6    250     655      0     1.098175  14.7806    0.0000     1.098175  1.26e-01  2.86e-01  5.47e+00  9.07e+00   0.0062   6.2479
Bin2+sSOS       8    310     775      0     1.053069  10.0661    0.0088     1.052976  8.62e-02  2.43e-01  4.18e+01  9.32e+01   0.0061  22.2671

Bin2+mSOS       4    310     805    120     1.180700  23.4061    0.0000     1.180700  8.07e-02  1.41e-01  2.49e+01  5.48e+01   0.0021   1.4480
Bin2+mSOS       6    430    1045    180     1.098175  14.7806    0.0000     1.098175  1.26e-01  2.86e-01  5.47e+00  9.07e+00   0.0023   4.7957
Bin2+mSOS       8    550    1285    240     1.053069  10.0661    0.0080     1.052984  8.62e-02  2.43e-01  4.18e+01  9.32e+01   0.0024  15.9864

Bin2+Saw        4    310    1075    120     0.985859   3.0414    0.0055     0.985805  1.15e-01  2.48e-01  2.65e+02  5.18e+02   0.0029   9.6450
Bin2+Saw        6    430    1495    180     0.958677   0.2004    0.0077     0.958603  7.52e-02  1.68e-01  8.94e+01  1.71e+02   0.0034  11.1699
Bin2+Saw        8    550    1915    240     0.956996   0.0247    0.0072     0.956927  7.52e-02  1.68e-01  1.37e+02  2.09e+02   0.0040  41.2888

HybS+sSOS       4    310    1165      0     0.812261  15.1030    0.0000     0.812261  5.52e-01  1.00e+00  2.04e+02  2.97e+02   0.0068   2.2300
HybS+sSOS       6    410    1545      0     0.891208   6.8515    0.0000     0.891208  5.49e-01  1.00e+00  3.69e+02  7.09e+02   0.0077   3.9774
HybS+sSOS       8    510    1925      0     0.934789   2.2965    0.0087     0.934707  5.48e-01  1.00e+00  3.47e+02  5.22e+02   0.0080  12.7141

HybS+mSOS       4    390    1345     80     0.812261  15.1030    0.0046     0.812224  5.52e-01  1.00e+00  2.04e+02  2.97e+02   0.0031   2.3325
HybS+mSOS       6    530    1805    120     0.891208   6.8515    0.0000     0.891208  5.49e-01  1.00e+00  3.69e+02  7.09e+02   0.0035   5.0967
HybS+mSOS       8    670    2265    160     0.934789   2.2965    0.0047     0.934744  5.48e-01  1.00e+00  3.47e+02  5.22e+02   0.0040  13.4526

HybS+Saw        4    390    1525     80     0.951869   0.5113    0.0084     0.951789  5.48e-01  1.00e+00  2.16e+03  4.23e+03   0.0034   8.7207
HybS+Saw        6    530    2105    120     0.956386   0.0391    0.0099     0.956291  5.48e-01  1.00e+00  4.57e+02  7.57e+02   0.0041  27.5456
HybS+Saw        8    670    2685    160     0.956734   0.0027    0.0078     0.956659  5.48e-01  1.00e+00  6.08e+00  1.07e+01   0.0049  81.7212

DNMDT           4    395    1640     80     0.954878   0.1967    0.0004     0.954874  1.39e-03  3.13e-03  4.70e-04  1.05e-03   0.0027   3.3448
DNMDT           6    550    2315    120     0.956636   0.0130    0.0098     0.956541  6.75e-05  1.57e-04  4.26e+03  9.54e+03   0.0031  14.4201
DNMDT           8    705    2990    160     0.956754   0.0007    0.0096     0.956662  4.62e-06  1.14e-05  9.42e+01  1.49e+02   0.0035  44.9251

==============================================================================================================================================

This branch

Network: 10 nodes, 13 edges, 3 cost segments
Generators: 5, Demands: 5
Loss coefficients (a, b, c) per generator:
  n1: a=0.007287  b=0.005968  c=0.003850
  n2: a=0.001094  b=0.009002  c=0.007028
  n3: a=0.007897  b=0.008552  c=0.003001
  n4: a=0.008179  b=0.002530  c=0.009637
  n5: a=0.009778  b=0.009934  c=0.009099

Solver logs: /home/runner/work/InfrastructureOptimizationModels.jl/InfrastructureOptimizationModels.jl/branch/test/performance/logs/solver_2026-06-24T00-57-48.log

==============================================================================================================================================
Bilinear Approximation Benchmarks
  Refinement = depth for all methods
==============================================================================================================================================
Method          R   Vars Constrs   Bins    Objective   Gap(%) MIPGap(%)     LowerBnd  rmse δbi   max δbi   rmse δq    max δq  build_t  solve_t
----------------------------------------------------------------------------------------------------------------------------------------------
NLP (Ipopt)     -     40     105      0     0.956760        -         -            -  0.00e+00  0.00e+00  0.00e+00  0.00e+00   0.0260   0.0040

NLP (Uno)       -     40     105      0     0.956760   0.0000         -            -  0.00e+00  0.00e+00  0.00e+00  0.00e+00   0.0012   0.0046

Bin2+sSOS       4    190     535      0     1.180700  23.4061    0.0000     1.180700  8.07e-02  1.41e-01  2.49e+01  5.48e+01   0.0058   1.4770
Bin2+sSOS       6    250     655      0     1.098175  14.7806    0.0000     1.098175  1.26e-01  2.86e-01  5.47e+00  9.07e+00   0.0060   6.1689
Bin2+sSOS       8    310     775      0     1.053069  10.0661    0.0088     1.052976  8.62e-02  2.43e-01  4.18e+01  9.32e+01   0.0057  21.9247

Bin2+mSOS       4    310     805    120     1.180700  23.4061    0.0000     1.180700  8.07e-02  1.41e-01  2.49e+01  5.48e+01   0.0022   1.4335
Bin2+mSOS       6    430    1045    180     1.098175  14.7806    0.0000     1.098175  1.26e-01  2.86e-01  5.47e+00  9.07e+00   0.0024   4.7550
Bin2+mSOS       8    550    1285    240     1.053069  10.0661    0.0080     1.052984  8.62e-02  2.43e-01  4.18e+01  9.32e+01   0.0026  15.6380

Bin2+Saw        4    310    1075    120     0.985859   3.0414    0.0055     0.985805  1.15e-01  2.48e-01  2.65e+02  5.18e+02   0.0032   9.4667
Bin2+Saw        6    430    1495    180     0.958677   0.2004    0.0077     0.958603  7.52e-02  1.68e-01  8.94e+01  1.71e+02   0.0038  11.0494
Bin2+Saw        8    550    1915    240     0.956996   0.0247    0.0072     0.956927  7.52e-02  1.68e-01  1.37e+02  2.09e+02   0.0041  41.0084

HybS+sSOS       4    310    1165      0     0.812261  15.1030    0.0000     0.812261  5.52e-01  1.00e+00  2.04e+02  2.97e+02   0.0071   2.2361
HybS+sSOS       6    410    1545      0     0.891208   6.8515    0.0000     0.891208  5.49e-01  1.00e+00  3.69e+02  7.09e+02   0.0068   3.9956
HybS+sSOS       8    510    1925      0     0.934789   2.2965    0.0087     0.934707  5.48e-01  1.00e+00  3.47e+02  5.22e+02   0.0074  12.7395

HybS+mSOS       4    390    1345     80     0.812261  15.1030    0.0046     0.812224  5.52e-01  1.00e+00  2.04e+02  2.97e+02   0.0029   2.3370
HybS+mSOS       6    530    1805    120     0.891208   6.8515    0.0000     0.891208  5.49e-01  1.00e+00  3.69e+02  7.09e+02   0.0034   5.1275
HybS+mSOS       8    670    2265    160     0.934789   2.2965    0.0047     0.934744  5.48e-01  1.00e+00  3.47e+02  5.22e+02   0.0038  13.1660

HybS+Saw        4    390    1525     80     0.951869   0.5113    0.0084     0.951789  5.48e-01  1.00e+00  2.16e+03  4.23e+03   0.0035   8.6321
HybS+Saw        6    530    2105    120     0.956386   0.0391    0.0099     0.956291  5.48e-01  1.00e+00  4.57e+02  7.57e+02   0.0041  27.3971
HybS+Saw        8    670    2685    160     0.956734   0.0027    0.0078     0.956659  5.48e-01  1.00e+00  6.08e+00  1.07e+01   0.0047  81.4176

DNMDT           4    395    1640     80     0.954878   0.1967    0.0004     0.954874  1.39e-03  3.13e-03  4.70e-04  1.05e-03   0.0027   3.3599
DNMDT           6    550    2315    120     0.956636   0.0130    0.0098     0.956541  6.75e-05  1.57e-04  4.26e+03  9.54e+03   0.0030  14.4539
DNMDT           8    705    2990    160     0.956754   0.0007    0.0096     0.956662  4.62e-06  1.14e-05  9.42e+01  1.49e+02   0.0035  45.3514

==============================================================================================================================================

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@jd-lara @rodrigomha