Given a list of items with different sizes, write an algorithm to pack these items into the minimum number of batches without exceeding the capacity of each batch.

This problem is a variation of the Bin Packing Problem, often addressed using greedy algorithms. A common approach is to sort the items by size in descending order. Then, iterate through the sorted items, placing each item into the first batch that has enough remaining capacity. If no existing batch can accommodate the item, a new batch is created for it. This greedy strategy aims to fill batches as much as possible before starting new ones, thereby minimizing the total number of batches used. For optimal solutions, more complex algorithms like First Fit Decreasing (FFD) or algorithms based on dynamic programming might be considered, but the greedy approach provides a good balance of efficiency and effectiveness for many practical scenarios.