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/*********************************************
== Holiday Packages  a Simulation ==
This program SIMULATES the problem of packing heavy objects
into boxes, which will then be shipped (perhaps by DHL).
There are 10 objects of various weights, e.g.
20 25 13 8 9 14 12 29 35 21
This is a very CHEAP simulation. The user must type
the POSITION of the object to put it into the box.
For example, you could fill a box EXACTLY full
by taking items #1 , #2 , and #6 making 50 kg exactly.
The goal is to use as few boxes as possible,
as each box must be paid for. Assume it is being shipped
with a fixed price per box, say 40 EU each.
Then every box you save means you saved 40 EU.
*************************************************/
public class PackBoxes {
int[] nums = new int[10];
int boxes = 0;
public PackBoxes() {
output("== Packing Boxes ==\n"
+ "Each box can hold 50 kg. \n"
+ "You must put objects (right) \n"
+ "into boxes, but don't exceed 50 kg.\n"
+ "Use as few boxes as possible."
);
makeNums();
do {
fillBox();
} while (checkDone() == false);
output("You used " + boxes + " boxes");
System.exit(0);
}
public void fillBox() {
boxes = boxes + 1;
int total = 50;
int contents = 0;
int choice = 1;
do {
String ask = input(allNums() + "\nChoose a position in the list (nothing to PACK):");
if (ask.length() == 0) {
choice = 1;
} else {
choice = Integer.parseInt(ask);
}
if (choice >= 10) {
output("Illegal position");
} else if (choice < 0) {
output("Packing the box now.");
} else if (nums[choice] <= total) {
contents = contents + nums[choice];
total = total  nums[choice];
nums[choice] = 0;
} else {
output("That is too heavy for this box.");
}
} while (choice >= 0);
output("That box contains " + contents + " kg.");
}
public void makeNums() {
nums[0] = random(5, 35);
nums[1] = random(5, 35);
nums[2] = random(5, 35);
nums[3] = random(5, 35);
nums[4] = random(5, 35);
nums[5] = random(5, 35);
nums[6] = random(5, 35);
nums[7] = random(5, 35);
nums[8] = random(5, 35);
nums[9] = random(5, 35);
}
public int random(int smallest, int largest) {
return (int) (Math.random() * (largest  smallest + 1) + smallest);
}
public String allNums() {
return (" " + nums[0] + " " + nums[1]
+ " " + nums[2] + " " + nums[3]
+ " " + nums[4] + " " + nums[5]
+ " " + nums[6] + " " + nums[7]
+ " " + nums[8] + " " + nums[9]);
}
public boolean checkDone() {
if (nums[0] > 0  nums[1] > 0  nums[2] > 0
 nums[3] > 0  nums[4] > 0  nums[5] > 0
 nums[6] > 0  nums[7] > 0  nums[8] > 0  nums[9] > 0) {
return false;
} else {
return true;
}
}
public static void main(String[] args) {
new PackBoxes();
}
public String input(String prompt) {
return javax.swing.JOptionPane.showInputDialog(null, prompt);
}
public void output(String message) {
javax.swing.JOptionPane.showMessageDialog(null, message);
}
java.awt.Font bigFont = new java.awt.Font("Verdana", java.awt.Font.BOLD, 24);
int useBigFonts = bigFonts();
public int bigFonts() {
javax.swing.UIManager.put(
"OptionPane.messageFont",
new javax.swing.plaf.FontUIResource(bigFont)
);
javax.swing.UIManager.put(
"OptionPane.buttonFont",
new javax.swing.plaf.FontUIResource(bigFont)
);
return 0;
}
}

This program doesn't actually do anything automtically, but it points
up the NEED for automation.
When you run the program, you must choose several items that will fit in
a box for a total weight
of 50 kg or less. Then pick items to pack into a second box.
Continue until all the items are
in a box. The goal is to use as few boxes as possible  don't pack
one item in each box!
When you are doing this, think about your own thinking. What are
you thinking when you try
to choose an optimal set of items? Do you just start with the
first item and second item and
then look for another that fits? Or do you just around in the
list, looking for a set that make
exactly 50?
/*********************************************** (0) Play the game (oops, RUN the SIMULATION) a few times to see how it works. Then make the changes listed below. (1) Change MAKENUMS so it uses a LOOP instead of 10 separate commands. (2) Change MAKENUMS so it uses bigger numbers  between 20 and 100. Then change the limits on a box to 100 kg. Then the game is more challenging. (3) Change the program to use 12 objects instead of 10. You will need to change several parts of the program. (4) Write a method called HELP. If the user types 99, the HELP method should run and SUGGEST an item that could still fit in the box. (4) Write a method called HELP. If the user types 99, the HELP method should run and SUGGEST an item that could still fit in the box. What is the ALGORITHM for making a good suggestion? (5) Write a GREEDY automatic algorihtm. It works like this: put the first item in the box if there is still room, put the next item in if there is still room, put the next item in continue until the next item won't fit once you reach this point, search through the rest of the array for a small enough item continue until no more items fit in the box Pack the box then repeat, starting at the first nonzero item. (6) Write a BETTER auto method. This time, the program searches for any PAIR of numbers that fill the box EXACTLY. Then pack them in the box and repeat. If there is no pair that fills the box, then try to find 3 items that will fill the box EXACTLY. If it's not possible to fill the box exactly, then try to fill it to MAX1. Then try MAX2, etc. The goal is to make the box as full as possible. This problem is an example of ARTIFICIAL INTELLIGENCE. This is nontrivial, especially if you want a"good" answer, or perhaps even "the best" answer. This is known by two different names for slightly different versions of the problem: (1) Knapsack problem  given a knapsack (backpack) and a set of weights, find a combination of weights that fills the knapsack exactly. This can be used as the basis of an ENCRYPTION algorithm, but was shown to be "breakable". (2) Partition problem  divide a set of weights into 2 or 3 or more "partitions" that all contain the same total  or, more realistically, divide the weights into some number of groups that are as evenly distributed as possible. These problems are "AI hard" problems, requiring far toomuch searching. ************************************************/