good starting point, working pulp

backend/src/utils/optimizer.py

@@ -2,7 +2,6 @@ import yaml, logging
 import numpy as np
 import pulp as pl
 from scipy.optimize import linprog
-from scipy.sparse import lil_matrix, csr_matrix
 from collections import defaultdict, deque
 
 from ..structs.landmark import Landmark
@@ -508,21 +507,14 @@ class Optimizer:
 
         # SET CONSTRAINTS FOR INEQUALITY
         c, A_ub, b_ub = self.init_ub_time(landmarks, max_time)  # Adds the distances from each landmark to the other.
-        print("ok1")
         self.respect_number(A_ub, b_ub, L, max_landmarks)       # Respects max number of visits (no more possible stops than landmarks).
-        print("ok2")
         self.break_sym(A_ub, b_ub, L)                           # Breaks the 'zig-zag' symmetry. Avoids d12 and d21 but not larger cirlces.
 
         # SET CONSTRAINTS FOR EQUALITY
-        print("ok3")
         A_eq, b_eq = self.init_eq_not_stay(landmarks)           # Force solution not to stay in same place
-        print("ok4")
         self.respect_start_finish(A_eq, b_eq, L)                # Force start and finish positions
-        print("ok5")
         self.respect_order(A_eq, b_eq, L)                       # Respect order of visit (only works when max_time is limiting factor)
-        print("ok6")
         self.respect_user_must(A_eq, b_eq, landmarks)           # Force to do/avoid landmarks set by user.
-        print("ok7")
 
         self.logger.debug(f"Optimizing with {A_ub.shape[0]} + {A_eq.shape[0]} = {A_ub.shape[0] + A_eq.shape[0]} constraints.")
 
@@ -545,14 +537,12 @@ class Optimizer:
             prob += (pl.lpSum([A_eq[i][j] * x[j] for j in range(L*L)]) == b_eq[i])
 
         # 6. Solve the problem
-        prob.solve(pl.PULP_CBC_CMD(msg=False))
+        prob.solve(pl.PULP_CBC_CMD(msg=False, gapRel=0.3))
 
         # 7. Extract Results
         status = pl.LpStatus[prob.status]
         solution = [pl.value(var) for var in x]  # The values of the decision variables (will be 0 or 1)
 
-        print(status)
-
         self.logger.debug("First results are out. Looking out for circles and correcting.")
 
         # Raise error if no solution is found. FIXME: for now this throws the internal server error