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All Journal IAES International Journal of Artificial Intelligence (IJ-AI)
Nindynar Rikatsih
Universitas Brawijaya
Computer Science & IT Engineering

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Optimization of agricultural product storage using real-coded genetic algorithm based on sub-population determination Wayan Firdaus Mahmudy; Nindynar Rikatsih; Syafrial Syafrial
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 11, No 3: September 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v11.i3.pp826-835

Abstract

The storage of fresh agricultural products is a combinatorial problem that should be solved to to maximize number of items in the storage and also maximize the total profit without exceed the capacity of storage. The problem can be addressed as a knapsack problem that can be classified as NP-hard problem. We propose a genetic algorithm (GA) based on sub-population determination to address the problem. Sub-population GA can naturally divide the population into a set of sub-population with certain mechanism in order to obtain a better result. GA based on sub-population is applied by generating a set of sub-population which is happened in the process of initializing population. A special migration mechanism is developed to maintain population diversity. The experiment shows GA based on sub-population determination provide better results comparable to those achieved by classical GA.
Co-Authors Syafrial Syafrial Wayan Firdaus Mahmudy