First working version of the new datastructures

src/MIP/SupportFunctions.jl

@@ -5,13 +5,12 @@ function buildJd(timeslots,subcal)
      timeslots |> @filter(_.dayID in keys(subcal))|>@groupby(_.resourceID) |>@map((d = key(_),j = unique(map(x->x.dayID,_)))) |> NDSparse
 end
 function buildI(timeslots)
-    timeslots |> @groupby((_.resourceID,_.dayID)) |> @map({d=key(_)[1],j=key(_)[2],i=map(x->x.timeslotID,_)})|> NDSparse
+    timeslots|> @filter(!_.booked) |> @groupby((_.resourceID,_.dayID)) |> @map({d=key(_)[1],j=key(_)[2],i=map(x->x.timeslotID,_)})|> NDSparse
 end
 
 
 function getTlowerbound(timeslots,resourceID,dayID)
-    println("$resourceID -  $dayID")
-    bookedslots = timeslots |> @filter(_.resourceID == resourceID && _.dayID == dayID && _.status )|> @orderby(_.endTime) |> @take(1)  |>@map(_.endTime) |> collect
+    bookedslots = timeslots |> @filter(_.resourceID == resourceID && _.dayID == dayID && _.booked )|> @orderby(_.endTime) |> @take(1)  |>@map(_.endTime) |> collect
     if length(bookedslots) == 1
         value = Dates.value(first(bookedslots))/60000000000
     else
@@ -56,7 +55,7 @@ end
 
 "Produces a IndexedTable of patient groups based on the function patientgroup()"
 function buildPg(patients,visits,Vp)
-    table(patients |> @groupby(patientgroup(visits,Vp,_.intID))|> @map((group1=key(_)[1],group2=key(_)[2],group3=key(_)[3],patients= map(x->x.intID,_))) |> collect)
+    table(patients |> @groupby(patientgroup(visits,Vp,_.intID))|> @map((types=key(_)[1],startmonth=key(_)[2],endmonths=key(_)[3],patients= map(x->x.intID,_))) |> collect)
 end
 
 

src/MIP/masterproblem.jl

@@ -8,7 +8,7 @@ function setupmaster(subproblems,patients,resources,timeslots,subMastercalendar,
 
     K = length(patients)
     Pg = sets.Pg
-    Gp = keys(Pg) ##TODO virker nok ikke men nu smutter jeg hjem
+    Gp = [i for i in 1:length(Pg)]
     D = JuliaDB.select(resources,:intID)
     J = keys(subMastercalendar)
     Jd = sets.Jd
@@ -27,10 +27,10 @@ function setupmaster(subproblems,patients,resources,timeslots,subMastercalendar,
     @constraint(master,consref_offtime[d in D, j in Jd[d]], sum(lambda[m]*1000 for m in 1:K) <= closingtime[d,j]) #TODO Only for consultations
 
     @constraint(master,convexitycons[g in Gp],
-       sum(lambda[m] for m in 1:K if m in Pg[g].patients) == length(P_g[g].patients) )
+       sum(lambda[m] for m in 1:K if m in Pg[g].patients) == length(Pg[g].patients) )
 
 
-    @constraint(master,consref_onepatient[ d in D, j in Jd[d], i in I[d,j]],
+    @constraint(master,consref_onepatient[ d in D, j in Jd[d].j, i in I[d,j].i],
         0 <=1 )
 
 

src/MIP/model_column.jl

@@ -2,7 +2,8 @@
 EPSVALUE = 0.1
 
 
-function columngeneration(patients, visits, resources, timeslots, mastercalendar, timeDelta, setuponly = false)
+function columngeneration(patients, visits, resources, timeslots, mastercalendar, timeDelta; setuponly = false, multithreading = false)
+    println("Building sets")
     timeslotsNDSparse = ndsparse(timeslots)
     subproblems = Subproblems()
     sets = Sets()
@@ -13,9 +14,9 @@ function columngeneration(patients, visits, resources, timeslots, mastercalendar
     sets.Jd = buildJd(timeslots,mastercalendar)
     sets.I = buildI(timeslots)
     sets.Pg = buildPg(patients,visits,sets.Vp)
-
+    println("Setting up sub-problems")
     setup_sub!(subproblems,patients,visits,resources,timeslotsNDSparse,mastercalendar,timeDelta,sets,1)
-
+    println("Setting up master")
     mp = setupmaster(subproblems,patients,resources,timeslots,mastercalendar,sets)
     #generateInitialColumns(mp,subproblems)
     if setuponly
@@ -26,6 +27,7 @@ function columngeneration(patients, visits, resources, timeslots, mastercalendar
     while !done
         iteration +=1
         println(iteration)
+        println("Solving master")
         optimize!(mp.model)
         println("Master objective value = $(JuMP.objective_value(mp.model))")
         println.(getPositiveVariables(mp.lambda))
@@ -39,24 +41,31 @@ function columngeneration(patients, visits, resources, timeslots, mastercalendar
         θ = dual.(mp.consref_onepatient)
         κ = dual.(mp.convexitycons)
 
-        subthreads = []
+        println("Solving subproblems")
+        if multithreading
+            subthreads = []
+            for sub in values(subproblems.pricingproblems)
+                push!(subthreads,Threads.@spawn solveSub!(sub,sets,ϕ,θ,κ))
+            end
+            #end
+            for thread in subthreads
+                wait(thread) #TODO remove multithreading, fix at turn MT back on
+            end
+        else
+            for sub in values(subproblems.pricingproblems)
+                solveSub!(sub,sets,ϕ,θ,κ)
+                # solveSub!(sub,ϕ,θ,κ)
+                # done2 = addcolumntomaster!(mp,sub,iteration,EPSVALUE) #TODO add patient info
+                # done &= done2
+                # count = 0
+                # while !done2 && count < 0#length(sub.patients)
+                #     count += 1
+                #     solveSub!(sub,getIndexofPositiveVariables(sub.xvars)) #TODO time this
+                #     done2 = addcolumntomaster!(mp,sub,iteration,EPSVALUE)
+                # end
+            end
+            #end
 
-        for sub in values(subproblems.pricingproblems)
-
-            push!(subthreads,Threads.@spawn solveSub!(sub,ϕ,θ,κ))
-            # solveSub!(sub,ϕ,θ,κ)
-            # done2 = addcolumntomaster!(mp,sub,iteration,EPSVALUE) #TODO add patient info
-            # done &= done2
-            # count = 0
-            # while !done2 && count < 0#length(sub.patients)
-            #     count += 1
-            #     solveSub!(sub,getIndexofPositiveVariables(sub.xvars)) #TODO time this
-            #     done2 = addcolumntomaster!(mp,sub,iteration,EPSVALUE)
-            # end
-        end
-        #end
-        for thread in subthreads
-            wait(thread)
         end
         done = addcolumntomaster!(mp,subproblems,iteration,EPSVALUE)
 

src/MIP/subproblem.jl

@@ -8,12 +8,12 @@
 function setup_sub!(subproblems,patients::IndexedTable,visits,resources::IndexedTable,timeslots,mastercalendar::Dict{Int,Date},TimeDelta,sets,months)
 
 
-    for patient in rows(patients)
+    for patientgroup in [i for i in 1:length(sets.Pg)]
 
         #TODO length of min treatment time should be calculated and used.
 
 
-        setup_sub!(subproblems,patient,visits,resources,timeslots,mastercalendar,TimeDelta,sets,months)
+        setup_sub!(subproblems,patientgroup,visits,resources,timeslots,mastercalendar,TimeDelta,sets,months)
     end
 end
 startofyear(date::Date) = Date(Year(date))
@@ -31,12 +31,12 @@ function getTimeDelta(timeDelta,visits,v1,v2)
 end
 
 
-function setup_sub!(subproblems,patient::NamedTuple,visits,resources::IndexedTable,timeslots,mastercalendar::Dict{Int,Date},timeDelta,sets,months)
+function setup_sub!(subproblems,p::Int64,visits,resources::IndexedTable,timeslots,mastercalendar::Dict{Int,Date},timeDelta,sets,months)
     M1 = 10
     M2 = 1000
 
     Td(v1,v2) = getTimeDelta(timeDelta,visits,v1,v2)
-    p = patient.intID
+
     V = sets.Vp[p].v; Dv = sets.Dv; D = sets.Dp[p].d; J = sets.J ;Jd = sets.Jd; I = sets.I
     Ts(d,j,i) = Dates.value(timeslots[d,j,i].startTime)/60000000000
     Te(d,j,i) = Dates.value(timeslots[d,j,i].endTime)/60000000000
@@ -46,11 +46,6 @@ function setup_sub!(subproblems,patient::NamedTuple,visits,resources::IndexedTab
     enddate = startdate + Month(months)-Day(1)
     subMastercalendar = MasterCalendar(mastercalendar,startdate,enddate)
 
-
-
-# TODO tilføj gruppering igen
-    #TODO input all the . notificatons
-
         sub = Model(with_optimizer(Gurobi.Optimizer,OutputFlag=0))
         @variable(sub,xvars[v in V,d in Dv[v].d,j in Jd[d].j,i in I[d,j].i],Bin)
         @variable(sub,yvars[j = J],Bin)
@@ -115,7 +110,7 @@ function solveSub!(sub,ϕ,θ,κ)
     optimize!(sub.model)
     status = termination_status(sub.model)
     if status != MOI.TerminationStatusCode(1)
-        println("$(minimum(sub.J)) - $(maximum(sub.J))")
+
         throw("Error: Non optimal sub-problem for subproblem $(sub.intID)")
 
         #TODO Throw warning and extend search area