Knapsack Problem (0-1 solution) - Dynamic Algorithm

Tue, 27 Sep 2016 00:00:00 +0000

I’ve recently dug up old code from my University days, which I thought I’d share for the benefit/misfortune of others.

There’s a common problem in programming called the knapsack problem. Here was my solution based on the dynamic algorithm.

# Math is used to floor/round the floats to an interger and back! import math

Total allowed weight

totalWeight = 2392;

Define the items name, Weight, Profit

items = ((“Weapon and Ammunition”, 4.13, 1.4), (“Water”, 2.13, 2.74), (“Pith Helmet”, 3.03, 1.55), (“Sun Cream”, 2.26, 0.82), (“Tent”, 3.69, 2.38), (“Flare Gun”, 3.45, 2.93), (“Olive Oil”, 1.09, 1.77), (“Firewood”, 2.89, 0.53), (“Kendal Mint Cake”, 1.08, 2.77), (“Snake Repellant Spray”, 3.23, 4.29), (“Bread”, 2.29, 2.85), (“Pot Noodles”, 0.55, 0.34), (“Software Engineering Textbook”, 2.82, -0.45), (“Tinned Food”, 2.31, 2.17), (“Pork Pie”, 1.63, 1.62))

Knapsack Problem (0-1 solution) - Greedy Algorithm

Tue, 27 Sep 2016 00:00:00 +0000

I’ve recently dug up old code from my University days, which I thought I’d share for the benefit/misfortune of others.

There’s a common problem in programming called the knapsack problem. Here was my solution based on the greedy algorithm.

# Name, Weight and Value of Items items = [(“Weapon and Ammunition”, 4.13, 1.4), (“Water”, 2.13, 2.74), (“Pith Helmet”, 3.03, 1.55), (“Sun Cream”, 2.26, 0.82), (“Tent”, 3.69, 2.38), (“Flare Gun”, 3.45, 2.93), (“Olive Oil”, 1.09, 1.77), (“Firewood”, 2.89, 0.53), (“Kendal Mint Cake”, 1.08, 2.77), (“Snake Repellant Spray”, 3.23, 4.29), (“Bread”, 2.29, 2.85), (“Pot Noodles”, 0.55, 0.34), (“Software Engineering Textbook”, 2.82, -0.45), (“Tinned Food”, 2.31, 2.17), (“Pork Pie”, 1.63, 1.62)]

Algorithms on Daniel Pomfret

Knapsack Problem (0-1 solution) - Dynamic Algorithm

Total allowed weight

Define the items name, Weight, Profit

Knapsack Problem (0-1 solution) - Greedy Algorithm