Hybrid Real-Coded Genetic Algorithm and Variable Neighborhood Search for Optimization of Product Storage - Rikatsih, Nindynar; Mahmudy, Wayan Firdaus; Syafrial, Syafrial (Journal of Information Technology and Computer Science, 2019)
Agricultural product storage has a problem that need to be noticedbecause it has an impact in gaining the profit according to the number ofproducts and the capacity of storage. Inappropriate combination of productcauses high expenses and low profit. To solve the problem, we propose geneticalgorithm (GA) as the optimization method. Although GA is good enough tosolve the problem, GA not always gives an optimum result in complex searchspaces because it is easy to be trapped in local optimum. Therefore, we presenta hybrid real-coded genetic algorithm and Variable Neighborhood Search(HRCGA-VNS) to solve the problem. VNS is applied after reproductionprocess of GA to repair the offspring and improve GA exploitation capabilitiesin local area to get better result. The test results show that the optimal popsizeof GA is 180, number of generations is 80, combination of cr and mr is 0.7 and0.3 while optimum Kmax of VNS is 40 with number of iterations 50. Eventhough HRCGA-VNS need longer computational time, HRCGA-VNS hasproven to provide a better result based on higher fitness value compared withclassical GA and VNS.