IMPLEMENTASI METODE BRANCH AND BOUND DAN ALGORITMA BRUTE FORCE PADA MODEL MULTIPLE CONSTRAINTS KNAPSACK PROBLEM TERHADAP AVERAGE RATING WEEKLY REPORT TV

The knapsack problem is a combinatorial optimization problem to find the best solution out of many solutions. knapsack problem is a matter of selecting items that have weight and value that will be inserted into the bag without exceeding the capacity of the bag. A knapsack problem that has more than one constraint is called the Multiple Constraints knapsack Problem (MCKP) which can be converted into a 0-1 knapsack problem model by combining MCKP constraints into one constraint. The knapsack problem is done by implementing the Branch and Bound of exact method and the Brute Force algorithm of heuristic method on the Average Rating Weekly Report TV data. The purpose of this study was to solve the MCKP using the Branch and Bound method and the Brute Force algorithm and to compare which results were more effective in using the MCKP solution. The optimal MCKP results obtained were 24.4 (in rating) and a total knapsack of 11,311.3. In this case, the capacity of knapsack filled by TV stations is METRO, RCTI, and TV ONE by 95.22%. Based on the problem-solving time, it is found that the Brute Force algorithm is more efficient than the Branch and Bound method.