Applying greedy genetic algorithm on 0/1 multiple knapsack problem

Vinod Jain, Jay Shankar Prasad
2018 International Journal of Advanced Technology and Engineering Exploration  
ACCENTS Umbarkar et al. [1] propose a genetic algorithm with the dual population to solve optimization problems. The application of dual population improves the performance of the genetic algorithm for solving these problems. It basically removes the problem of Research Article Abstract Knapsack problem is a well-known optimization problem in computer science. It has many application areas in science and engineering. Knapsack problem can be solved using genetic algorithm. Multiple knapsack
more » ... em (MKP) is a special form of knapsack problem in which items are to be placed in more than one knapsack. Many researchers solve MKP problem using different techniques such as ant colony optimization (ACO), particle swarm optimization (PSO) and genetic algorithm (GA). The objective of this paper is to solve MKP problem using GA in an efficient manner. In this paper MKP is solved using greedy genetic algorithm. The proposed genetic algorithm uses greedy approach in its selection and reproduction operations of GA. The proposed greedy genetic algorithm is implemented on a standard data set and results ensure that the proposed greedy algorithm performs better than the standard genetic algorithm. Keywords Multiple knapsack problem, Genetic algorithm, Greedy approach.
doi:10.19101/ijatee.2018.545018 fatcat:tzxnc46v5ja3lmkqtnmxsdwawe