Grey Wolf Optimizer and Whale Optimization Algorithm for Stochastic Inventory Management of Reusable Products in a two-level Supply Chain
Amir Hossein Sadeghi, Erfan Amani Bani, Ali Fallahi

TL;DR
This paper introduces a new stochastic inventory management problem for reusable products in a supply chain, applying novel metaheuristics (GWO and WOA) and statistical validation to find effective solutions.
Contribution
It formulates a complex nonlinear model with uncertainty and proposes GWO and WOA as innovative solution methods, validated against an exact algorithm.
Findings
GWO outperforms WOA in solution quality
Both algorithms perform comparably to the exact method
Metaheuristics effectively handle stochastic constraints
Abstract
Product reuse and recovery is an efficient tool that helps companies to simultaneously address economic and environmental dimensions of sustainability. This paper presents a novel problem for stock management of reusable products in a single-vendor, multi-product, multi-retailer network. Several constraints, such as the maximum budget, storage capacity, number of orders, etc., are considered in their stochastic form to provide a more realistic framework. The presented problem is formulated as a constrained nonlinear mathematical model. The chance-constrained programming method is suggested to deal with the constraints' uncertainty. Regarding the nonlinearity of the model, grey wolf optimizer (GWO) and whale optimization algorithm (WOA) as two novel metaheuristics are presented as solution approaches, and the sequential quadratic programming (SQP) exact algorithm validates their…
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Taxonomy
TopicsOptimization and Mathematical Programming
