Algorithmic paradigm that builds up a solution piece by piece, always choosing the next piece that offers the most obvious and immediate benefit. So the problems where choosing locally optimal also...

Extracted text: Algorithmic paradigm that builds up a solution piece by piece, always choosing the next piece that offers the most obvious and immediate benefit. So the problems where choosing locally optimal also leads to global solution are best fit for Greedy. For example consider the Fractional Knapsack Problem. Cook is going on an excursion and requirements to apply for between locale and between state travel e-passes. It requires A minutes to fill each between region e-pass application and B minutes for each between state e-pass application. His excursion is given to you as a paired string S of length N where 0 signifies crossing starting with one locale then onto the next area (which needs a between region e-pass), and a 1 indicates crossing starting with one state then onto the next (which needs a between state e-pass). Figure out the all-out opportunity Cooks needs to spend on filling the different structures. Demonstrate the coding behavior.