Problem statement
The current design has major problems for large models, that is models with a large number of Nodes and Links. The problem originates in the approach we utilize for mapping from caseᵣₕ to case for saving the results through the function original. The filter functionality here is called for each index of a variable.
As an example, if we want to get the results for the variable :cap_use in a single operational period for a system with 336 operational periods and 10 000 nodes, we have a 10 000 if-loops for the nodes over 10 000 nodes and 10 000 if loops for the 336 operational periods. And these results only account for a single operational period and variable.
Proposed solution
The mapping should instead be based on dictionary to avoid the for loop
Problem statement
The current design has major problems for large models, that is models with a large number of
Nodes andLinks. The problem originates in the approach we utilize for mapping fromcaseᵣₕtocasefor saving the results through the functionoriginal. The filter functionality here is called for each index of a variable.As an example, if we want to get the results for the variable
:cap_usein a single operational period for a system with 336 operational periods and 10 000 nodes, we have a 10 000 if-loops for the nodes over 10 000 nodes and 10 000 if loops for the 336 operational periods. And these results only account for a single operational period and variable.Proposed solution
The mapping should instead be based on dictionary to avoid the for loop