## Hybrid Real-Coded Genetic Algorithm and Variable Neighborhood Search for Optimization of Product Storage

#### Author

Nindynar Rikatsih, Wayan Firdaus Mahmudy, Syafrial Syafrial Download PDF#### Abstract

Agricultural product storage has a problem that need to be noticedbecause it has an impact in gaining the profit according to the number of

products and the capacity of storage. Inappropriate combination of product

causes high expenses and low profit. To solve the problem, we propose genetic

algorithm (GA) as the optimization method. Although GA is good enough to

solve the problem, GA not always gives an optimum result in complex search

spaces because it is easy to be trapped in local optimum. Therefore, we present

a hybrid real-coded genetic algorithm and Variable Neighborhood Search

(HRCGA-VNS) to solve the problem. VNS is applied after reproduction

process of GA to repair the offspring and improve GA exploitation capabilities

in local area to get better result. The test results show that the optimal popsize

of GA is 180, number of generations is 80, combination of cr and mr is 0.7 and

0.3 while optimum Kmax of VNS is 40 with number of iterations 50. Even

though HRCGA-VNS need longer computational time, HRCGA-VNS has

proven to provide a better result based on higher fitness value compared with

classical GA and VNS.

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DOI: http://dx.doi.org/10.25126/jitecs.201942111