Instance 90_05 using the simple decomposition
NODES
TIME
avg
min
avg
min
l_l_l_o_n 343.20 343.00 0.06 0.06
S_s_l_c_n 162.20 162.00 0.04 0.04
L_l_l_c_n 162.60 160.00 0.04 0.04
S_e_l_c_n 162.80 162.00 0.04 0.04
S_s_m_c_n 165.40 162.00 0.04 0.04
d_l_l_o_n 16468058.00 1504.00 961.22 0.11
L_s_m_c_n 168.40 164.00 0.04 0.04
R_s_m_c_n 165.20 162.00 0.04 0.04
S_l_l_o_n 343.00 343.00 0.05 0.05
L_l_m_o_n 335.60 335.00 0.05 0.05
s_e_l_c_n 167.60 166.00 0.04 0.03
s_l_l_c_n 163.20 162.00 0.03 0.03
pq_l_m_o_n 330.00 330.00 0.04 0.04
mo_s_l_c_n 14015208.60 1541.00 768.77 0.09
mo_s_m_c_n 88358.40 1452.00 4.76 0.11
r_l_m_o_n 339.40 339.00 0.04 0.04
S_l_m_o_n 330.00 330.00 0.05 0.05
l_s_l_c_n 167.60 166.00 0.05 0.03
r_s_m_c_n 167.80 166.00 0.04 0.04
s_s_m_c_n 168.00 165.00 0.03 0.03
l_l_l_c_n 163.20 162.00 0.05 0.04
pq_l_l_o_n 310362.00 310362.00 18.80 18.73
d_s_l_c_n 165.20 164.00 0.04 0.04
R_e_m_c_n 166.20 164.00 0.04 0.04
pq_l_l_c_n 4322719.20 160.00 240.33 0.03
s_l_l_o_n -- -- -- --
l_l_m_o_n 341.20 340.00 0.06 0.05
S_l_m_c_n 163.80 163.00 0.04 0.04
pq_e_l_c_n 4421454.20 160.00 240.29 0.03
R_l_l_o_n 346.20 341.00 0.05 0.05
R_s_l_c_n 162.80 162.00 0.04 0.04
R_l_m_c_n 164.20 164.00 0.04 0.04
d_l_m_c_n 8275997.80 162.00 480.39 0.03
s_l_m_o_n 1518.00 1405.00 0.12 0.12
pq_s_m_c_n 200.00 153.00 0.04 0.04
pq_s_l_c_n 514.20 160.00 0.05 0.03
r_l_m_c_n 168.80 167.00 0.04 0.03
L_l_m_c_n 172.80 171.00 0.04 0.04
d_s_m_c_n 164.00 161.00 0.04 0.03
R_l_m_o_n 343.00 343.00 0.05 0.05
r_e_l_c_n 167.60 166.00 0.04 0.03
s_l_m_c_n 169.60 167.00 0.03 0.03
s_e_m_c_n 168.00 165.00 0.03 0.03
L_e_m_c_n 168.60 164.00 0.04 0.04
L_e_l_c_n 163.40 162.00 0.04 0.04
d_l_m_o_n -- -- -- --
R_l_l_c_n 162.60 160.00 0.04 0.04
l_s_m_c_n 169.40 167.00 0.05 0.04
L_l_l_o_n 343.00 343.00 0.05 0.05
r_s_l_c_n 167.60 166.00 0.04 0.03
r_e_m_c_n 167.80 166.00 0.04 0.03
l_l_m_c_n 169.00 168.00 0.04 0.04
R_e_l_c_n 163.40 162.00 0.04 0.04
d_e_m_c_n 163.60 160.00 0.04 0.03
r_l_l_c_n 163.20 162.00 0.04 0.04
d_e_l_c_n 166.20 165.00 0.04 0.03
S_l_l_c_n 162.60 160.00 0.04 0.04
S_e_m_c_n 165.40 162.00 0.04 0.04
pq_e_m_c_n 210.60 206.00 0.04 0.04
pq_l_m_c_n 210.60 206.00 0.04 0.04
l_e_m_c_n 169.40 167.00 0.05 0.05
l_e_l_c_n 167.60 166.00 0.05 0.04
s_s_l_c_n 167.60 166.00 0.04 0.03
d_l_l_c_n 168.00 167.00 0.04 0.03
r_l_l_o_n 346.80 346.00 0.05 0.05
L_s_l_c_n 162.20 162.00 0.04 0.03

Best configurations

['L_e_l_c_n', 'L_e_m_c_n', 'L_l_l_c_n', 'L_l_l_o_n', 'L_l_m_c_n', 'L_l_m_o_n', 'L_s_l_c_n', 'L_s_m_c_n', 'R_e_l_c_n', 'R_e_m_c_n', 'R_l_l_c_n', 'R_l_l_o_n', 'R_l_m_c_n', 'R_l_m_o_n', 'R_s_l_c_n', 'R_s_m_c_n', 'S_e_l_c_n', 'S_e_m_c_n', 'S_l_l_c_n', 'S_l_l_o_n', 'S_l_m_c_n', 'S_l_m_o_n', 'S_s_l_c_n', 'S_s_m_c_n', 'd_e_l_c_n', 'd_e_m_c_n', 'd_l_l_c_n', 'd_s_l_c_n', 'd_s_m_c_n', 'l_e_l_c_n', 'l_e_m_c_n', 'l_l_l_c_n', 'l_l_l_o_n', 'l_l_m_c_n', 'l_l_m_o_n', 'l_s_l_c_n', 'l_s_m_c_n', 'mo_s_m_c_n', 'pq_e_m_c_n', 'pq_l_l_o_n', 'pq_l_m_c_n', 'pq_l_m_o_n', 'pq_s_l_c_n', 'pq_s_m_c_n', 'r_e_l_c_n', 'r_e_m_c_n', 'r_l_l_c_n', 'r_l_l_o_n', 'r_l_m_c_n', 'r_l_m_o_n', 'r_s_l_c_n', 'r_s_m_c_n', 's_e_l_c_n', 's_e_m_c_n', 's_l_l_c_n', 's_l_m_c_n', 's_l_m_o_n', 's_s_l_c_n', 's_s_m_c_n']

Description

Each table represents some statics related to given configuration. A configuration is denoted by A_B_C_D_E where :
  1. A is the selection criteria. We denote by
    • mo : Max option
    • pq : The capacity q\p
    • d : The residual demand
    • l : The load
    • s : The slack
    • r : The usage rate
  2. B is the aggregation function. We denote by
    • l : Lexicographic order
    • s : Sum of the elements
    • e : Euclidean norm
  3. C is the exploration criteria. We denote by
    • l : Lexicographic exploration
    • m : Middle towars sides
  4. D is the Branching parameter. We denote by
    • o : Option
    • c : Class
  5. E is the filtering model. We denote by
    • n : The default model using sum constraints
    • am : The model using the AtMostSeqCard Constraint
    • gs : The model using the Global Sequencing Constraint (GSC)
    • gsam : The model combining AtMostSeqCard+GSC
    • f : The model using the new filtering algorithm

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