<![CDATA[Every person would want maximum profit with as little as possible resources or capital. One example in everyday life is the problem of limited storage media but is required to get the maximum benefit. From this problem comes the term known as the knapsack problem. One of the problems with Knapsack is knapsack 0- 1, where knapsack 0-1 is a problem of storing goods where the item will be completely inserted or not at all. Completion of knapsack 0-1 problems can be helped using a metaheuristic algorithm. Metaheuristic algorithms include the Penguins Search Optimization (PeSOA) algorithm and the Migration Birds Optimization (MBO) algorithm. This study aims to determine the resolution of knapsack 0-1 problems using the Penguins Search Optimization (PeSOA) algorithm and the Migration Birds Optimization (MBO) algorithm and compare the optimal solutions obtained. This research method is divided into three main parts. First take data that includes the name of the item, the purchase price, the selling price and the weight of each item. The second is applying the Penguins Search Optimization (PeSOA) algorithm and the Migration Birds Optimization algorithm (MBO) on 0-1 knapsack problems. The third program is made to facilitate the calculation of data with the help of Matlab R2015b software. The results of this study found that both algorithms both reached the optimal solution, but the convergence and running time obtained were different. The Migrating Birds Optimization (MBO) algorithm is faster converging than the Penguins Search Optimization (PeSOA) algorithm to get the optimal solution. And also the Migrating Birds Optimization (MBO) algorithm has better running time than the Penguins Search Optimization (PeSOA) algorithm to achieve maximum iteration. Keywords: Whale optimization algorithm, multi knapsack 0-1 problem with multiple constraints.]]>
