Update main.py

main.py

@@ -110,7 +110,7 @@ def calculate_project_kpis(**params):
     cumulative_cash_flow = np.cumsum(cash_flows)
     payback_period_years = np.where(cumulative_cash_flow > 0)[0]
     payback_period = payback_period_years[0] + 1 if len(payback_period_years) > 0 else float('inf')
-    annual_profit = np.mean([cf for cf in cash_flows[1:] if cf > 0]) if any(cf > 0 for cf in cash_flows[1:]) else np.nan  # FIX: جلوگیری از nan
+    annual_profit = np.mean([cf for cf in cash_flows[1:] if cf > 0]) if any(cf > 0 for cf in cash_flows[1:]) else np.nan 
 
     return {"irr": irr, "annual_profit": annual_profit, "total_capex": total_capex, "payback_period": payback_period}
 
@@ -124,11 +124,11 @@ def run_optimizations_without_ml():
 
 def run_genetic_algorithm():
     print("Running Genetic Algorithm (GA)...")
-    random.seed(42)  # FIX: reproducibility
-    population = [{k: random.choice(v) if isinstance(v, list) else random.uniform(*v) for k,v in OPTIMIZATION_SPACE.items()} for _ in range(40)]
+    random.seed(42) 
+    population = [{k: random.choice(v) if isinstance(v, list) else random.uniform(*v) for k,v in OPTIMIZATION_SPACE.items()} for _ in range(25)]
     best_overall_individual = None
     best_overall_fitness = -float('inf')
-    for _ in range(80):
+    for _ in range(50):
         fitnesses = [calculate_project_kpis(**ind)['irr'] for ind in population]
         if max(fitnesses) > best_overall_fitness:
             best_overall_fitness = max(fitnesses)
@@ -157,7 +157,7 @@ def run_bayesian_optimization():
     @use_named_args(skopt_space)
     def objective(**params):
         return -calculate_project_kpis(**params)['irr']
-    res = gp_minimize(objective, skopt_space, n_calls=90, random_state=42, n_initial_points=20)
+    res = gp_minimize(objective, skopt_space, n_calls=50, random_state=42, n_initial_points=20)
     best_params = {space.name: val for space, val in zip(skopt_space, res.x)}
     kpis = calculate_project_kpis(**best_params)
     return {"Method": "Bayesian Opt", **kpis, "Params": best_params}
@@ -174,7 +174,7 @@ def run_optuna_direct():
         }
         return calculate_project_kpis(**params)['irr']
     study = optuna.create_study(direction="maximize")
-    study.optimize(objective, n_trials=150, n_jobs=-1)
+    study.optimize(objective, n_trials=100, n_jobs=-1)
     kpis = calculate_project_kpis(**study.best_params)
     return {"Method": "Optuna (TPE - Direct)", **kpis, "Params": study.best_params}