Algoritma Elephant Herding Optimization: Permasalahan Multiple Constraints Knapsack 0-1

Elephant Herding Optimization Algorithm: Multiple Constraints Knapsack 0-1 Problems

Abstract

Optimization problems are often found in everyday life, such as when determining goods to be a limited storage media. This causes the need for the selection of goods in order to obtain profits with the requirements met. This problem in mathematics is usually called a knapsack. Knapsack problem itself has several variations, in this study knapsack type used is multiple constraints knapsack 0-1 which is solved using the Elephant Herding Optimization (EHO) algorithm. The aim of this study is to obtain an optimal solution and study the effectiveness of the algorithm comparing it to the Simplex method in Microsoft Excel. This study uses two data, consisting of primary and secondary data. Based on the results of parameter testing, the proven parameters are nClan, nCi,α,β and MaxGen have a significant effect. The final simulation results have also shown a comparison of the EHO algorithm with the Simplex method having a very small percentage deviation. This shows that the EHO algorithm is effective for completing optimization multiple constraints knapsack 0-1.

Keywords: EHO Algorithm, Multiple Constraints Knapsack 0-1 Problem.