I have published my paper “Comparison of Optimisation Methods for The Knapsack Problem: Steepest Ascent Hill Climbing vs. Simulated Annealing” on ResearchGate.
The paper explores the application of optimization algorithms, specifically Hill Climbing and Simulated Annealing, to solve the knapsack problem. The knapsack problem is a well-known combinatorial optimization problem with various real-world applications. The aim is to select a subset of items with maximum value while adhering to a weight constraint. The paper provides a comparative analysis of the two algorithms, evaluates their performance based on metrics such as best solution, average solution, and iterations required to converge, and identifies the optimal solution. Additionally, it includes a literature review discussing the application areas of the knapsack problem and concludes with the limitations of the chosen search methods and potential avenues for further development.
Link to the paper:
