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

Sadeghi, Amir Hossein; Bani, Erfan Amani; Fallahi, Ali; Handfield, Robert

doi:10.1109/access.2023.3269292

Cited by 20 publications

(4 citation statements)

References 56 publications

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“…The goal of policy analysis is to provide decision-makers with relevant information and insights that can help them make informed decisions about policy choices. Policy analysis is a versatile tool that can be applied in a variety of fields, including healthcare (Sahebi-Fakhrabad et al, 2023), natural resource management (Yoosefdoost et al, 2022), sustainable supply chain (Sadeghi, Bani, et al, 2023), social welfare, and more, to provide valuable insights into policy design and implementation. Policy analysis is a crucial aspect of effective warehouse management, particularly when it comes to selecting the optimal lane depth.…”

Section: Literature Reviewmentioning

confidence: 99%

Optimizing warehouse operations for environmental sustainability: A simulation study for reducing carbon emissions and maximizing space utilization

Sadeghi¹,

Nikfar²,

Rad³

2024

10.5267/j.jfs

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Loading and unloading operations for Stock Keeping Units (SKUs) in warehouses are critical to logistics management systems. However, these operations also have a significant impact on the environment, particularly in terms of carbon dioxide (CO2) emissions. As such, warehouse management must consider not only operational efficiency but also environmental impact. The reduction of CO2 emissions in warehouses is becoming increasingly important, both for legal compliance and to meet sustainability targets. In this article, we will emphasize the environmental impact of warehouse operations, particularly on CO2 emissions, and explore ways to minimize them while still maximizing warehouse performance. We will review various optimization models proposed to address this issue and highlight the importance of considering environmental objectives when designing warehouse operations. We will also describe a simulation study conducted to determine the Pareto optimal frontier for a warehouse design, considering transportation, space utilization, and CO2 emissions. The outcomes of implementing this simulation's results include reduced CO2 emissions and increased space utilization, which demonstrate the potential benefits of considering environmental objectives in warehouse design and management.

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Section: Literature Reviewmentioning

confidence: 99%

Optimizing warehouse operations for environmental sustainability: A simulation study for reducing carbon emissions and maximizing space utilization

Sadeghi¹,

Nikfar²,

Rad³

2024

10.5267/j.jfs

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“…2023 22 [94] This paper proposes the integration of the Grey Wolf Optimizer and Whale Optimization Algorithm to address stochastic inventory management challenges in a two-level supply chain for reusable products. By combining both algorithms, it enhances inventory control strategies, optimizing stock levels and minimizing costs in dynamic supply chain environments.…”

Section: Reference Description Yearmentioning

confidence: 99%

WOA: Wombat Optimization Algorithm for Solving Supply Chain Optimization Problems

Benmamoun,

Khlie,

Dehghani

et al. 2024

Mathematics

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Supply Chain (SC) Optimization is a key activity in today’s industry with the goal of increasing operational efficiency, reducing costs, and improving customer satisfaction. Traditional optimization methods often struggle to effectively use resources while handling complex and dynamic Supply chain networks. This paper introduces a novel biomimetic metaheuristic algorithm called the Wombat Optimization Algorithm (WOA) for supply chain optimization. This algorithm replicates the natural behaviors observed in wombats living in the wild, particularly focusing on their foraging tactics and evasive maneuvers towards predators. The theory of WOA is described and then mathematically modeled in two phases: (i) exploration based on the simulation of wombat movements during foraging and trying to find food and (ii) exploitation based on simulating wombat movements when diving towards nearby tunnels to defend against its predators. The effectiveness of WOA in addressing optimization challenges is assessed by handling the CEC 2017 test suite across various problem dimensions, including 10, 30, 50, and 100. The findings of the optimization indicate that WOA demonstrates a strong ability to effectively manage exploration and exploitation, and maintains a balance between them throughout the search phase to deliver optimal solutions for optimization problems. A total of twelve well-known metaheuristic algorithms are called upon to test their performance against WOA in the optimization process. The outcomes of the simulations reveal that WOA outperforms the other algorithms, achieving superior results across most benchmark functions and securing the top ranking as the most efficient optimizer. Using a Wilcoxon rank sum test statistical analysis, it has been proven that WOA outperforms other algorithms significantly. WOA is put to the test with twenty-two constrained optimization problems from the CEC 2011 test suite and four engineering design problems to showcase its ability to solve real-world optimization problems. The results of the simulations demonstrate that WOA excels in real-world applications by delivering superior solutions and outperforming its competitors.

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“…Reusable products are designed to be used multiple times, reducing the need for constant replacements [38]. By encouraging reuse, these products minimize the environmental impact associated with manufacturing, transportation, and disposal [39]. Reusable products can include items such as shopping bags, water bottles, coffee cups, and food containers, providing consumers with sustainable choices that reduce their reliance on disposable options [38].…”

mentioning

confidence: 99%

“…Reusable products can include items such as shopping bags, water bottles, coffee cups, and food containers, providing consumers with sustainable choices that reduce their reliance on disposable options [38]. By embracing reusable products, individuals can significantly contribute to waste reduction and the conservation of resources, ultimately promoting a more sustainable and environmentally friendly lifestyle [39].…”

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confidence: 99%

Unveiling Sustainability in Ecommerce: GPT-Powered Software for Identifying Sustainable Product Features

2023

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In recent years, the concept of sustainability has gained significant attention across various industries. Consumers are increasingly concerned about the environmental impact of the products they purchase, leading to a growing demand for sustainable options. However, identifying sustainable product features can be a complex and time-consuming task. This paper presents a novel approach to address this challenge by utilizing GPT (Generative Pre-trained Transformer) powered software for automatically identifying sustainable product features from product descriptions, titles, and product specifications. The software leverages the power of natural language processing and machine learning to classify products into different sustainability categories. By analyzing the textual information provided, the software can extract key sustainability indicators, such as eco-friendly materials, energy efficiency, recyclability, and ethical sourcing. This automated process eliminates the need for manual assessment and streamlines the evaluation of product sustainability. The proposed software not only empowers consumers to make informed and sustainable purchasing decisions but also facilitates businesses in showcasing their environmentally friendly offerings. The experimental results demonstrate the effectiveness and accuracy of the software in identifying sustainable product features. The primary objective of this article is to assess the suitability of the GPT model for the domain of sustainability assessment. By collecting a real-life dataset and employing a specific methodology, four hypotheses are formulated, which will be substantiated through the experimental outcomes. This research contributes to the field of sustainability assessment by combining advanced language models with product classification, paving the way for a more sustainable and eco-conscious future.

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

Cited by 20 publications

References 56 publications

Optimizing warehouse operations for environmental sustainability: A simulation study for reducing carbon emissions and maximizing space utilization

Optimizing warehouse operations for environmental sustainability: A simulation study for reducing carbon emissions and maximizing space utilization

WOA: Wombat Optimization Algorithm for Solving Supply Chain Optimization Problems

Unveiling Sustainability in Ecommerce: GPT-Powered Software for Identifying Sustainable Product Features

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