Project 2 - Optimization - Duplicate

priority = [ 2, 6, 1, 7, 10, 8, 5] time = [30,200,20,70,120,60, 150] # # define number of tasks: don't hardwire this but rather use the len() command n_tasks = len(priority) max_time = 8*60 print ( f"TASK PRIORITY TIME TO COMPLETE") # you need to add an appropriate for loop here and modify the next print statement so that you can print out all tasks for i in range(n_tasks): high_priority = priority.index(min(priority)) time_priority = time[high_priority] print (f" {i+1} {priority[high_priority]} {time[high_priority]}") priority.pop(high_priority) time.pop(high_priority)

test_list = [ 4, 5, 3, 7, 11, 2] max_value = max(test_list) # use function max() to find maximum value in list max_index = test_list.index(max_value) # use method list.index () to find the index where this max occurs print(f" {max_value} is the highest test in the list and has an index of {max_index}") # print out results in formatted statement

test_list = [ 4, 5, 3, 7, 11, 2] time_list = [30, 45, 20, 120, 90, 70 ] max_value = max(test_list) max_index = test_list.index(max_value) task_time = time_list[max_index] # input the time it takes to complete this task print(f" {max_value} is the highest test in the list and has an index of {max_index} and takes {task_time} minutes") # print out values as in Step #2 plus the time it takes to complete task

max_time = 6 * 60 # this is not the maximum time available for your example but rather for testing time_used = 3 * 60 # # Following 6 statements are from Step 3 test_list = [ 4, 5, 3, 7, 11, 2] time_list = [30, 45, 20, 120, 90, 70 ] max_value = max(test_list) max_index = test_list.index(max_value) task_time = time_list[max_index] print(f"{max_value} is the highest test in the list and has an index of {max_index} and takes {task_time} minutes") # # Add conditional to see if this task can be completed in the allotted time if ((time_used+task_time) < max_time) : time_used += task_time print(f"Added Test {max(test_list)} with total used time of {time_used} minutes") # if conditional is true, i.e., task can be completed update time_used # add print statements

# Input problem specific data and print it out from Step 1 priority = [ 2, 6, 1, 7, 10, 8, 5] time = [30,200,20,70,120,60, 150] # # define number of tasks: don't hardwire this but rather use the len() command # Finds number of tasks n_tasks = len(priority) # Max time 8 hours * 60 minutes = 480 minutes max_time = 8*60 # Prints out the header of the table print ( f"TASK PRIORITY TIME TO COMPLETE") # you need to add an appropriate for loop here and modify the next print statement so that you can print out all tasks #Prints the table out in order as presented in list for i in range(n_tasks): print (f" {i+1} {priority[i]} {time[i]}") # # Initialize any variables before loop # Initialize the time used as 0 used_time = 0 # # add for loop to go through all tasks # For loop for greedy algorithm for i in range(n_tasks) : # find highest priority left and task number it corresponds to from Step 3/4 # Finds maximum's index in list representing the highest priority and the time associated with it high_priority = priority.index(max(priority)) time_priority = time[high_priority] # If statement to check if task time can fit in to used time and not over max time if (used_time+time_priority <= max_time): # add used time to variable used_time += time_priority # Print out statement showing which task was added and time associated. Print total used time print(f"Added task {priority[high_priority]} with {time_priority} used and with total used time of {used_time}") # Zero out both task priority and time as it is added to used time priority[high_priority] = 0 time[high_priority] = 0 # # Print out the total time used for all tasks in day 1 print(f"Finished day 1 using {used_time} minutes")

# Input problem specific data and print it out from Step 1 priority = [ 2, 6, 1, 7, 10, 8, 5] time = [30,200,20,70,120,60, 150] # # define number of tasks: don't hardwire this but rather use the len() command # Finds number of tasks n_tasks = len(priority) # Max time 8 hours * 60 minutes = 480 minutes max_time = 8*60 # Prints out the header of the table print ( f"TASK PRIORITY TIME TO COMPLETE") # you need to add an appropriate for loop here and modify the next print statement so that you can print out all tasks #Prints the table out in order as presented in list for i in range(n_tasks): print (f" {i+1} {priority[i]} {time[i]}") # # Initialize any variables before loop # Initialize the time used as 0 used_time = 0 task_number = 0 # # add for loop to go through all tasks # For loop for greedy algorithm for i in range(n_tasks) : # find highest priority left and task number it corresponds to from Step 3/4 # Finds maximum's index in list representing the highest priority and the time associated with it high_priority = priority.index(max(priority)) time_priority = time[high_priority] # If statement to check if task time can fit in to used time and not over max time if (used_time+time_priority <= max_time): # add used time to variable used_time += time_priority task_number += 1 # Print out statement showing which task was added and time associated. Print total used time print(f"Added task {priority[high_priority]} with {time_priority} minutes used and with total used time of {used_time}") # Zero out both task priority and time as it is added to used time priority[high_priority] = 0 time[high_priority] = 0 # If statement to check if used_time summed with the time is greater or equal to max_time if (used_time+time_priority >= max_time): # breaks the for loop break # # Print out the total time used for all tasks in day 1 print(f"Finished day 1 using {used_time} minutes and completed {task_number} tasks.")

# Input problem specific data old_priority = [ 2, 6, 1, 7, 10, 8, 5] time = [30,200,20,70,120,60, 150] n_tasks = len(old_priority) # # Create new priority list containing ratios # priority = [] # initialize the list which contains the new priorities which are original priority divided by # time it takes to complete this task for i in range(n_tasks): priority.append(old_priority[i]/time[i]) # Remainder of code should be the same; this is because we called the new list which contained the ratios the same as # before. max_time = 8*60 # Prints out the header of the table print ( f"TASK PRIORITY TIME TO COMPLETE") # you need to add an appropriate for loop here and modify the next print statement so that you can print out all tasks #Prints the table out in order as presented in list for i in range(n_tasks): print (f" {i+1} {round(priority[i],3)} {time[i]}") # # Initialize any variables before loop # Initialize the time used as 0 used_time = 0 task_number = 0 # # add for loop to go through all tasks # For loop for greedy algorithm for i in range(n_tasks) : # find highest priority left and task number it corresponds to from Step 3/4 # Finds maximum's index in list representing the highest priority and the time associated with it high_priority = priority.index(max(priority)) time_priority = time[high_priority] # If statement to check if task time can fit in to used time and not over max time if (used_time+time_priority <= max_time): # add used time to variable used_time += time_priority task_number += 1 # Print out statement showing which task was added and time associated. Print total used time print(f"Added task {priority.index(priority[high_priority])+1} with {time_priority} minutes used and with total used time of {used_time}") # Zero out both task priority and time as it is added to used time priority[high_priority] = 0 time[high_priority] = 0 # If statement to check if used_time summed with the time is greater or equal to max_time if (used_time+time_priority >= max_time): # breaks the for loop break # # Print out the total time used for all tasks in day 1 print(f"Finished day 1 using {used_time} minutes and completed {task_number} tasks.")