2023-04-25 ノースカロライナ州立大学(NCState)
ヒューリスティックアルゴリズムを使った研究で、GWOとWOAは、正確な最適化モデルと比べて、0.01％〜0.07％以内のコストを提供し、平均的には、正確な最適化モデルの半分の時間で解決策を提供できることがわかった。これにより、予期せぬ混乱に対応するために、ノードの再配置が必要な場合には、ヒューリスティックアルゴリズムが正確な最適化モデルよりも優れていることがわかった。
＜関連情報＞
- https://news.ncsu.edu/2023/04/fast-supply-chain-answers/
- https://ieeexplore.ieee.org/document/10106258
2階層サプライチェーンにおける再利用可能な製品の確率的在庫管理のためのGrey Wolf OptimizerとWhale Optimization Algorithm 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,Robert Handfield
IEEE Access Published:21 April 2023
DOI:https://doi.org/10.1109/ACCESS.2023.3269292
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 establish a more realistic problem. The presented problem is formulated using a nonlinear programming mathematical model. The chance-constrained approach 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 performance. The parameters of algorithms are calibrated using the Taguchi method for the design of experiments. Extensive analysis is established by solving several numerical results in different sizes and utilizing several comparison measures. Also, the results are compared statistically using proper parametric and non-parametric tests. The analysis of the results shows a significant difference between the algorithms, and GWO has a better performance for solving the presented problem. In addition, both algorithms perform well in searching the solution space, where the GWO and WOA differences with the optimal solution of the SQP algorithm are negligible.
