![]() On my machine, I get the following performances: In : % timeit solve_random_minmax ( 50, pulp. lpSum (]) >= a dot_B_x lp_prob = condition, label lp_prob. lpSum ( * x for j in range ( n )]) condition = pulp. for i in range ( n ): label = "Max_constraint_ %d " % i dot_B_x = pulp. ![]() lpSum (]), "Minimize_the_maximum" a, B = 2 * pylab. LpProblem ( "Compute internal torques", pulp. COIN_CMD ())Įasy access to all these solvers opens the way for testing: which one is theįastest? For this purpose, let us rewrite solve_minmax() quickly: def solve_random_minmax ( n, solver ): x = pulp. The other, replace the call to solve() in the function above by the solver Here on my machine, only COIN_CMD and GLPK_CMD passed the tests. Testing zero subtraction Testing continuous LP solution Testing maximize continuous LP solution. To check what solvers are available on your PuLP is actually a wrapping library that generates input files for various LP ![]()
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