meta-heuristic algorithms
Vida Karbasi bonab; Mahdi Yousefi Nejad Attari; Ensiyeh Neishabouri
Abstract
Vendor managed inventory (VMI) is one of the popular strategies to manage inventory control system, in this strategy, the vendor is responsible for controlling and replenishment the inventory of retailers. In this paper, a bi-objective vendor managed inventory (BOVMI) model with fuzzy demand was investigated ...
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Vendor managed inventory (VMI) is one of the popular strategies to manage inventory control system, in this strategy, the vendor is responsible for controlling and replenishment the inventory of retailers. In this paper, a bi-objective vendor managed inventory (BOVMI) model with fuzzy demand was investigated for a supply chain problem with multiple vendors and retailers, the fuzzy demand is formulated using trapezoidal fuzzy number (TrFN) where the centroid defuzzification method is employed to defuzzify fuzzy output functions. The vendor confronts two constraints: number of orders and available budget and minimizing the total inventory cost and optimizing the warehouse space are the two objectives of the model. Since the proposed model is formulated ino a bi-objective integer nonlinear programming (INLP) problem, an non-dominated Sorting genetic algorithm-II (NSGA-II) has been developed to find Pareto front solution. To improve the performance of algorithm has been calibrated using Taguchi method. Finally, conclusions are made and future research works are recommended.