Solving 0-1 knapsack problem by continuous ACO algorithm

Authors:
Chiranjit Changdar;G. S. Mahapatra;Rajat Kumar Pal
Affiliations:
Department of Computer Science, Raja N.L. Khan Women's College, Midnapore, Paschim Medinipur, West Bengal, 721102, India;Department of Mathematics, National Institute of Technology, Puducherry, Karaikal-609605, Puducherry, India;Department of Computer Science and Engineering, University of Calcutta, Calcutta 700 009, West Bengal, India
Venue:
International Journal of Computational Intelligence Studies
Year:
2013

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Abstract

This paper presents a continuous ACO approach to solve 0-1 knapsack problem. In this method, groups of candidate values of the components are constructed, and an amount of pheromone is initialised randomly for each candidate value a real random number between 0.1 and 0.9 in each candidate group. To solve binary knapsack problem for each object a candidate group is constructed where candidate value is either 0 or 1. Each ant selects a value from each group to construct a path or a solution. After certain number of generation, store the best solution in a temporary population. When temporary population size is equal to the number of ants, then temporary population will be considered as initial population by re-initialising fresh set of pheromone. This procedure will continue until the maximum generation defined is reached. In experimental section, we compare the results of standard test functions and 0-1 knapsack problem with existing literature.