Grey Wolf Optimizer and Whale Optimization Algorithm for Stochastic Inventory Management of Reusable Products in a Two-Level Supply Chain

Product reuse and recovery is an efficient tool that helps companies to simultaneously address economic environmental dimensions of sustainability. This paper presents a novel problem for stock management reusable products in single-vendor, multi-product, multi-retailer network. Several constraints, such as the maximum budget, storage capacity, number orders, etc., are considered their stochastic form establish more realistic problem. The presented formulated using nonlinear programming mathematical model. chance-constrained approach suggested deal with constraints’ uncertainty. Regarding nonlinearity model, grey wolf optimizer (GWO) whale optimization algorithm (WOA) two metaheuristics solution approaches, sequential quadratic (SQP) exact validates performance. parameters algorithms calibrated Taguchi method design experiments. Extensive analysis established by solving several numerical results different sizes utilizing comparison measures. Also, compared statistically proper parametric non-parametric tests. shows significant difference between algorithms, GWO has better performance In addition, both perform well searching space, where WOA differences optimal SQP negligible.