Downloaded 1,379 times
Uploaded byCaisar Oentoro
Greedy algorithm
Greedy algorithms make locally optimal choices at each step to try to find a global optimum. They choose the best option available at each state. For the travelling salesman problem, the greedy approach is to always choose the nearest unvisited city from the current city to build the route. While greedy algorithms are simple to implement, they do not always find the true optimal solution, especially for large complex problems, as they only consider the best choice at each step rather than the overall route.
In this document
Powered by AI
Introduction by Caisar Oentoro.
Greedy algorithms make locally optimal choices at each stage to find global optimum.
Discusses the Travelling Salesman Problem (TSP) for explaining greedy algorithms.
TSP aims to find the shortest route visiting all cities exactly once before returning.
Starts from city A, goes to nearest city B as the first optimization step.
From city B, selects city C next, emphasizing the nearest unvisited choice.
From city C, the algorithm chooses city D, again based on proximity.
Reaches city D, then backtracks to A as all cities have been visited.
Greedy algorithms are easy to implement and often provide the best solution in simple cases.
In complex problems, greedy may not yield the best solution and can be slower than other methods.
More Related Content
![UiPath Automation Suite Installation (Hands-On) [2/3]](https://cdn.slidesharecdn.com/ss_thumbnails/automationsuitecommunitysession2-251015095633-a6d862f1-thumbnail.jpg?width=600ounds&width=560&fit=bounds)
Greedy algorithm
- 1. Short Explanation, CaisarOentoro
- 2. What is GreedyAlgorithm? In the hard words: A greedy algorithm is an algorithm that follows the problem solving heuristics of making the locally optimal choice at each stage with the hope of finding a global optimum. (src: http://en.wikipedia.org/wiki/Greedy_algorithm) Simplify: Choose the best choice that ‘reachable’ at current state
- 3. Sample Usage ofGreedy For better explanation we use old simple problem: Travelling Salesman Problem:
- 4. TSP The Problemis how to travel from city A and visit all city on the map, then back to city A again. The rules: you only visit each city once and you can’t pass through any traversed path.
- 5. Solution: Find theshortest path from city A(start) to any other city. A B Because the nearest city is B, so we go to B
- 6. From B,we find any other city but A(because A has been visited) that has nearest path. So we choose C: A B C Keep tuning on…
- 7. From C,we look to nearest city again, but don’t look for A and B, because both has been visited. So we choose D. A B C D Soon end…
- 8. At thisnode(D), we can’t go to any city, because all neighbor of D has been visited. We go back to first city(A). A B C D And that was how to solve TSP problem.
- 9. Advantage of Greedy Greedy is easy to be implemented. Just search the best choice from the current state that ‘reachable’ (has any paths or any connections). In simple case, greedy often give you the best solution.
- 10. Drawback of Greedy In large and complex case, greedy doesn’t always give you the best solution, because it’s just search and take the best choice that you can reach from the current state. It takes longer time than any other algorithms for big case of problem