Probability collectives algorithm for solving knapsack problem

Abstract

       Combinatorial optimization problems are very common in various fields. It involves finding the best possible solution from a finite set of objects. Simply put, it is the process of identifying the optimal solutions from a set of available data sets for a particular problem. The knapsack problem (KP) is considered a familiar and thoughtful problem in combinatorial optimization, where it is used to model industrial situations or financial decisions. In this paper, we implement the approach of a Probability collective algorithm (PCA) for solving the knapsack problems (KP), which has achieved high performance.