Optimizing Array Jumps with Greedy Strategy

Day 12: 90-Day Coding Challenge 🚀 Continuing the journey of sharpening problem-solving skills, today I focused on array manipulation and optimization techniques. Today’s problem involved finding the minimum jumps to reach the end of an array, where each element represents the maximum steps you can move forward from that position. Instead of using a recursive or DP approach, I implemented a greedy strategy: • Tracked the farthest reachable index at each step • Maintained the current jump range, only incrementing jumps when reaching the end of this range • Iterated through the array efficiently to ensure the minimum number of jumps • By the end, the total jumps represent the optimal path to reach the last index This approach emphasizes thinking ahead and managing ranges, rather than checking every possible path. Time Complexity: O(n) Space Complexity: O(1) Today’s learning highlights: ✅ Explored greedy optimization for minimum jumps ✅ Practiced tracking ranges to reduce unnecessary computations ✅ Strengthened understanding of forward-looking strategies in arrays ✅ Improved problem-solving efficiency and approach flexibility It’s fascinating to see how array-based problems can be tackled in multiple ways while keeping time and space efficient 💡 Excited for Day 13 and more problem-solving challenges! #90DaysOfCode #DataStructures #Algorithms #Greedy #CodingJourney #Python #ProblemSolving #ArrayProblems

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