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Using 'exists' for loops over sparse arrays Description The models loop.mos/looph.mos and proj.mos show the effect of using the
keyword exists in conditions on loops over sparse arrays. As can be seen, the careful formulation of loops may result in a considerable speedup of the model execution time. Mosel defines two forms of sparse arrays, namely dynamic arrays and hashmap arrays. The model sparsearrays.mos compares the performance of these two forms for different cases of enumerations. Further explanation of this example:
'Mosel User Guide', Appendix 'Good modeling practice' explains in detail the correct use of exists.
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Data Files loop.mos (!******************************************************* Mosel Example Problems ====================== file loop.mos ````````````` Demonstrate effect of `exists' (c) 2008 Fair Isaac Corporation author: S. Heipcke, 2002, rev. Nov. 2021 *******************************************************!) model "loop" uses "mmsystem" public declarations R1,R2,R3,R4,R5: range Cost: dynamic array(R1,R2,R3,R4,R5) of real x: dynamic array(R1,R2,R3,R4,R5) of mpvar end-declarations ! This would normally be read in from a file Cost(1,1,1,1,1) := 1.1 Cost(1,30,1,3,3) := 2.2 Cost(1,1,30,1,4) := 3.3 Cost(1,1,1,30,1) := 4.4 Cost(1,6,1,1,30) := 5.5 Cost(30,1,1,1,3) := 6.6 forall(i1 in R1, i2 in R2, i3 in R3, i4 in R4, i5 in R5 | exists(Cost(i1,i2,i3,i4,i5)) ) create(x(i1,i2,i3,i4,i5)) starttime:=gettime ! 'exists' is not required here from a logical point of view, since the ! sum will only contain the variables that have been created, but it ! helps speeding up things. Compare the running times with and without it: sum(i1 in R1, i2 in R2, i3 in R3, i4 in R4, i5 in R5 | exists(Cost(i1,i2,i3,i4,i5)) ) Cost(i1,i2,i3,i4,i5) * x(i1,i2,i3,i4,i5) = 1 writeln("Time using `exists': ", gettime-starttime) sum(i1 in R1, i2 in R2, i3 in R3, i4 in R4, i5 in R5 ) Cost(i1,i2,i3,i4,i5) * x(i1,i2,i3,i4,i5) = 1 writeln("Time without `exists': ", gettime-starttime) ! Display the resulting constraint definitions on screen exportprob("") end-model | |||||||||||||||||

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