Optimization of a non-instantaneous deteriorating inventory problem with time and price dependent demand over finite time horizon via hybrid DESGO algorithm

This work presents an inventory model with partial backlogged shortages for deteriorating items over finite time horizon. Here, the deterioration rate is considered as a random variable which follows three-parameter Weibull distribution. Also, the demand rate is dependent on time and selling price of the product. The aim of this work is to determine the optimal selling price of the product, optimal number of replenishment cycle and maximum shortage level which maximize the retailer's total profit over the finite time horizon. To maximize the total profit, a new hybrid algorithm is proposed which is based on differential evolution and social group optimization algorithms. This algorithm is named as DESGO algorithm. In this context, a numerical problem, based on the proposed inventory model, is considered and solved by DESGO algorithm. To test the performance and efficiency of the proposed algorithm, the problem is solved by some other popular metaheuristic algorithms available in the existing literature and the obtained numerical results are compared with that of the DESGO algorithm. To justify the comparison, two different non-parametric statistical tests and also ANOVA test are conducted. From these tests, it is observed that the proposed hybrid algorithm performs well. Moreover, the impact of changes of different model parameters on the best-found policy is graphically through the sensitivity analysis. Finally, the work is concluded with some fruitful future scopes.