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| # Define the total production capacity function | |
| def calculate_total_production(a, b, c, ex, ez): | |
| # Calculate X, Y, Z | |
| work_speed = 155 # 75+50+30 | |
| work_speed_nocturnal = 175 # 75+50+30+20 | |
| X = work_speed * 10 * a + work_speed_nocturnal * 5 * ex + work_speed * 3 | |
| Y = work_speed * 10 * b | |
| Z = work_speed_nocturnal * (10 * c + 3 * ez) | |
| p = min (X,Y,Z) / Z # product quantity reduction | |
| # Calculate base product quantity | |
| base_product_quantity = p * ( 3 * 10 * c + 2 * 3 * (ex + ez)) / 30 * (100 + 35 * (ex+ez)) / 100 | |
| # Total production capacity | |
| total_capacity = min(X, Y, Z) / work_speed * base_product_quantity | |
| return total_capacity | |
| # Initialize results for the revised problem | |
| revised_results = [] | |
| # Iterate through n from 4 to 50 | |
| for n in range(4, 51): | |
| max_capacity = -999 | |
| best_solution = None | |
| # Iterate through all possible values of a, b, c, ex, ez | |
| for a in range(n): | |
| for b in range(n): | |
| for c in range(n): | |
| for ex in range(n): | |
| ez = n - a - b - c - ex - 1 | |
| if ez >= 0 and min (b, c + ez) != 0: # Ensure all variables are non-negative integers and has profits | |
| total_capacity = calculate_total_production(a, b, c, ex, ez) | |
| if total_capacity > max_capacity: | |
| max_capacity = total_capacity | |
| best_solution = (a, b, c, ex, ez) | |
| # Store the best solution for this n | |
| if best_solution: | |
| revised_results.append((n, best_solution, max_capacity, max_capacity / n)) | |
| print(revised_results) |
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