A Comparative Review of Classical Sorting Algorithms for Efficient Data Processing

This paper presents a comprehensive comparative analysis of classical sorting algorithms used in computer science. It evaluates both comparison-based algorithms (Bubble Sort, Insertion Sort, Selection Sort, Quick Sort, Merge Sort, Heap Sort, Shell Sort, Cocktail Sort, Comb Sort) and non-comparison-based algorithms (Counting Sort, Radix Sort, Bucket Sort). The study compares algorithms based on time complexity, space complexity, stability, adaptability, and real-world performance on various datasets including integers, decimals, and character data. Results show that Merge Sort and Heap Sort provide consistent O(n log n) performance, while Counting Sort and Bucket Sort achieve near-linear performance under specific conditions. The paper also discusses hybrid sorting techniques, GPU-based optimizations, and machine learning-based algorithm selection as future research directions.