MO Emulator: fix no-solution case #239

Don't recompute objectives when no solution available

include/mp/backend-std.h

@@ -474,7 +474,7 @@ class StdBackend :
   /// to AMPL via SOL file
   virtual void ReportSolution2AMPL() {
     double obj_value = std::numeric_limits<double>::quiet_NaN();
-    auto sol = GetSolution();             // even if just dual
+    auto sol = GetSolution();             // even if just dual or infeasible
     fmt::MemoryWriter writer;
     writer.write("{}: {}", MP_DISPATCH( long_name() ), SolveStatus());
     if (IsProblemSolvedOrFeasible()) {

include/mp/common.h

@@ -300,6 +300,10 @@ enum Status {
   INTERRUPTED = SPECIFIC
 };
 
+/// Status string ("solved", ...).
+/// Major status only.
+const char* GetStatusName(sol::Status stt);
+
 /** Following the taxonomy of the enum sol::Status, returns true if
       we have an optimal solution or a feasible solution for a
       satisfaction problem */

include/mp/flat/converter_multiobj.h

@@ -92,13 +92,16 @@ class MOManager {
   void ProcessMOIterationUnpostsolvedSolution(pre::ModelValuesDbl& sol) {
     if (IsMOActive()) {
       auto& objs = sol.GetObjValues()();
-      assert(1 == objs.size());
-      objval_last_ = objs.front();           // 0. save emulated obj value
+      if (objs.size())
+        objval_last_ = objs.front();           // 0. save emulated obj value
       // @todo 1. check if the solver correctly reports the current emulated obj
       // 2. Let's recompute the original objectives
-      objs.resize( MPCD(num_objs()) );
-      for (int i=0; i<(int)objs.size(); ++i)
-        objs[i] = ComputeValue(MPCD(get_obj(i)), sol.GetVarValues()());
+      const auto& xx = sol.GetVarValues()();
+      if (xx.size()) {                         // This can be invoked w/o solution
+        objs.resize( MPCD(num_objs()) );
+        for (int i=0; i<(int)objs.size(); ++i)
+          objs[i] = ComputeValue(MPCD(get_obj(i)), xx);
+      }
     }
   }
 
@@ -187,11 +190,9 @@ class MOManager {
       if (!proc_sol.first) {
         if (MPD( GetEnv() ).verbose_mode())
           MPD( GetEnv() ).Print(
-              "\n"
-              "MULTI-OBJECTIVE MODE: objective {} (out of {}):\n"
-              "    ABORTING due to the previous iteration's solve result ({}).\n"
+              "   ... ABORTING: previous iteration's solve result: {} (code {}.)\n"
               "==============================================================================\n\n"
-              , i_current_obj_+1, obj_new_.size(), proc_sol.second);
+              , sol::GetStatusName(proc_sol.second), proc_sol.second);
         return false;
       }
       RestrictLastObjVal();

solvers/highsmp/highsmpbackend.cc

@@ -346,6 +346,9 @@ std::pair<int, std::string> HighsBackend::GetSolveResult() {
   auto obj = Highs_getObjectiveValue(lp());
   auto inf = Highs_getInfinity(lp());
   bool hasSol = (-inf < obj && obj < inf);
+  int primal_solution_status;
+  Highs_getIntInfoValue(lp(),
+                        "primal_solution_status", &primal_solution_status);
   switch (optstatus) {
   case kHighsModelStatusOptimal:
     return { sol::SOLVED, "optimal solution" };
@@ -359,6 +362,8 @@ std::pair<int, std::string> HighsBackend::GetSolveResult() {
     return { sol::LIMIT_INF_UNB, "unbounded or infeasible" };
   case kHighsModelStatusModelError:
   case kHighsModelStatusLoadError:
+    if (kHighsSolutionStatusInfeasible == primal_solution_status)   // HiGHS 7
+      return { sol::INFEASIBLE, "infeasible problem" };
     return { sol::FAILURE, "solver error" };
   case kHighsModelStatusPresolveError:
   case kHighsModelStatusSolveError:

src/solver.cc

@@ -20,7 +20,9 @@
  Authors: Victor Zverovich, Gleb Belov
  */
 
+#include <map>
 #include <cctype>
+#include <climits>
 #include <cstdarg>
 #include <cstdio>
 #include <cstdlib>
@@ -237,6 +239,27 @@ void RSTFormatter::HandleDirective(const char *type) {
 
 namespace mp {
 
+namespace sol {
+
+const char* GetStatusName(sol::Status stt) {
+  static const std::map<int, const char*> stt_map {
+      { INT_MIN, "wrong_status_code" },
+      { NOT_SET, "not_set" },
+      { UNKNOWN, "unknown" },
+      { SOLVED, "solved" },
+      { UNCERTAIN, "solved?" },
+      { INFEASIBLE, "infeasible" },
+      { UNBOUNDED, "unbounded" },
+      { LIMIT, "limit" },
+      { FAILURE, "failure" }
+  };
+  auto it = stt_map.lower_bound(stt);
+  assert(stt_map.end() != it);
+  return it->second;
+}
+
+}
+
 namespace internal {
 
 void FormatRST(fmt::Writer &w,

test/end2end/cases/categorized/fast/iis_feasrelax/airtrainee_base.mod

@@ -0,0 +1,59 @@
+
+set I;              # Trainees
+set T;              # Training sessions
+set V{I} in T;      # Valid sessions for each trainee
+set Pos;            # Positons
+set PosPlus;        # Meta-positions (e.g, All, Cockpit, Cabin)
+set MAXPlusWhich{Pos} in PosPlus;
+
+param P{I} in Pos;  # Trainee's position
+param S{I};         # Seniority (smaller value <=> higher seniority)
+param L{I};         # Language (0 - both, 1 or 2 - one only)
+param E{I};         # Expiration: 0 - this month, 1 - next month, 2 - in 2 months
+param Pr{I, T};     # Priority: 0 - not wanted, larger value <=> higher preference
+param MAX{Pos};     # Position capacity
+param MAXPlus{PosPlus};  # Aggregated capacities (All, CK, CB)
+
+var x{i in I, t in T} binary <= if t in V[i] then 1 else 0;
+var y{i in I} binary <= if E[i]>0 then 1 else 0;      # Trainee i unassigned
+var u{T} binary;    # 1 <=> language 1, 0 <=> language 2
+var w >=0;          # Number of unassigned trainees
+
+s.t. Assign_E0 {i in I: E[i]==0}:
+  sum {t in V[i]} x[i, t] == 1;
+
+s.t. Unassigned_E12 {i in I: E[i]>0}:
+  sum {t in V[i]} x[i, t] + y[i] == 1;
+
+s.t. Sum_Unassigned: w == sum {i in I: E[i]>0} y[i];
+
+s.t. Language_1 {t in T}:
+  u[t]<0.5 ==> sum {i in I: L[i]==1 and t in V[i]} x[i, t] <= 0;
+
+s.t. Language_2 {t in T}:
+  u[t]>=0.5 ==> sum {i in I: L[i]==2 and t in V[i]} x[i, t] <= 0;
+
+s.t. Capacity {p in Pos, t in T}:
+  sum {i in I: p==P[i] and t in V[i]} x[i, t] <= MAX[p];
+
+s.t. Capacity_Meta {p in PosPlus, t in T}:
+  sum {i in I: p in MAXPlusWhich[P[i]] and t in V[i]} x[i, t] <= MAXPlus[p];
+
+suffix objpriority;
+param S_range := max {i in I} S[i] - min {i in I} S[i];
+
+# The primary objective
+minimize Total_Unassigned: w suffix objpriority 3*S_range + 1;
+# let Total_Unassigned.objpriority := card(I) + 3;
+
+# Trainee preferences, ranked by seniority
+set SenLevels := setof {i in I} S[i];
+param prefMax {i in I} := max {t in V[i]} Pr[i, t];
+minimize PrefViolRanked {s in SenLevels}:
+  sum {i in I: s==S[i]}
+    (1.0                                               # penalty 1 for non-assignment
+     - sum {t in V[i]: Pr[i, t]>0}
+       Pr[i, t] / prefMax[i]                           # normalize
+        * x[i, t]
+     + sum {t in V[i]: Pr[i, t]==0} x[i, t])           # penalty 2 for unwanted assignment
+    suffix objpriority max {j in I} S[j] + 2*S_range + 1 - s;