Exponential back-off is useful in cases where simultaneous attempts to do something will interfere with each other such that none succeed. In such cases, having devices randomly attempt an operation in a window which is too small will result in most attempts failing and having to be retried. Only once the window has grown large … Read more
Add in an auxiliary variable, say x4, with constraints: x4 >= c1*x1 x4 >= c2*x2 x4 >= c3*x3 Objective += c4*x4
UPDATE: The answer has become somewhat outdated in the past 4 years, here is an update. You have many options: If you do not have to do it Python then it is a lot more easier to do this in a modeling langage, see Any good tools to solve integer programs on linux? I personally … Read more
You need preserve index values by reset_index and parameter id_vars: df2 = pd.melt(df.reset_index(), id_vars=”index”,value_vars=[‘asset1′,’asset2′]) print (df2) index variable value 0 coper1 asset1 1 1 coper2 asset1 3 2 coper3 asset1 5 3 coper1 asset2 2 4 coper2 asset2 4 5 coper3 asset2 6 Then pivot working nice: print(df2.pivot(index=’index’,columns=”variable”, values=”value”)) variable asset1 asset2 index coper1 1 … Read more
I personally found GLPK better (i.e. faster) than LP_SOLVE. It supports various file formats, and a further advantage is its library interface, which allows smooth integration with your application.
To approach this problem, I would use an integer programming framework and define three sets of decision variables: x_ij: A binary indicator variable for whether we build a bridge at water location (i, j). y_ijbcn: A binary indicator for whether water location (i, j) is the n^th location linking island b to island c. l_bc: … Read more
Pulp is a python modeling interface that hooks up to solvers like CBC(open source), CPLEX (commercial), Gurobi(commercial), XPRESS-MP(commercial) and YALMIP(open source). You can also use Pyomo to model the optimization problem and then call an external solver, namely CPLEX, Gurobi GLPK and the AMPL solver library. You can also call GLPK from GLPK/Python, PyGLPK or … Read more