Solving 0/1 Knapsack Problem Using Metaheuristic Techniques

Knapsack problem has gained popularity in the field of combinatorial optimization. In this paper, different types of problem instances were selected. Two each of S-Metaheuristic methods and P-Metaheuristic methods were applied on the problem instances. S-Metaheuristics were applied to both the small problems and large problems while P-Metaheuristics were applied on only the large problems. Simulated Annealing and Iterated Local Search were tested on the problem instances and the results were compared. Also, Genetic Algorithm and Particle Swarm Optimization were compared. The techniques perform excellently with slight differences in the efficiency and time.