Solving the 0/1 Knapsack Problem Using Metaheuristic and Neural Networks for the Virtual Machine Placement Process in Cloud Computing Environment

Table 5

Time complexity analysis of metaheuristic algorithms for the Knapsack problem.

Algorithms	Time complexity
B&B
DP	, where W is the maximum weight in the knapsack
GA	, where N is the population size
ACO	, where N is the number of ants
SA	, where k is the number of iterations
TS	, where k is the number of iterations
Greedy
PSO	, where k is the number of iterations and N is the number of particles
NNA	, where N is the number of training samples

where n is the number of items in the knapsack.