Green Supply Chain Network Design with Emphasis on Inventory Decisions

Mahjoob, M. J.; Fazeli, Seyed Sajjad; Milanlouei, Soodabeh; Mohammadzadeh, Ali Kamali; Tavassoli, Leyla Sadat

doi:10.48550/arxiv.2104.05924

Cited by 2 publications

(3 citation statements)

References 13 publications

(18 reference statements)

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“…Constraints [9][10][11][12] are related to the capacity of raw material and product transportation vehicles and guarantee the minimum ability of transportation vehicles. Constraints [13][14][15] are related to facility location, whereas constraints [16][17][18] limit the number of distribution centers, 201 Designing a Green Supply Chain Transportation System for an Automotive ... plants, and temporary warehouses. Finally, constraints [19] and [20] are the logical constraints of the model.…”

Section: Mathematical Model Equationsmentioning

confidence: 99%

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Designing a Green Supply Chain Transportation System for an Automotive Company Based On Bi-Objective Optimization

Syah

Nasution

Shol

et al. 2022

Foundations of Computing and Decision Sciences

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Recently, due to the increasing awareness of communities regarding environmental issues and environmental regulations, companies have evolved to provide products with lower prices and better quality to retain and attract customers. Economics should also pay attention to environmental goals. Therefore, it is essential to provide a supply chain model that can consider both economic and environmental objectives. In this paper, the green direct supply chain network is presented to an automotive company, including five suppliers, primary warehouses, manufacturing plants, distributors, and sales centers. The objectives of this model are to minimize the total cost of construction, transportation, and the amount of carbon dioxide emissions during forwarding network transportation at all levels. The proposed model is also drawn using the weight method, which is one of the methods for solving multi-objective problems, and the solution of the model part. Ultimately, it has been discussed how much the automobile company should focus on reducing carbon dioxide so that managers can determine the best solutions from the Pareto border according to their organization’s priorities, which can be environmental or financial.

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Section: Mathematical Model Equationsmentioning

confidence: 99%

“…In this respect, they presented a bi-objective formulation where multiple inventory components were integrated into the location and routing decisions throughout the supply chain network. Notably, revolutionary algorithms were used to solve the model [18].…”

Section: Introductionmentioning

confidence: 99%

Designing a Green Supply Chain Transportation System for an Automotive Company Based On Bi-Objective Optimization

Syah

Nasution

Shol

et al. 2022

Foundations of Computing and Decision Sciences

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“…The genetic algorithm is a stochastic optimization technique inspired by the process of natural selection, which is widely applied to solve different classes of NP-Hard problems [15,16,17,18]. GA maintains a population of candidate solutions through the selective procedure.…”

Section: Modified Genetic Algorithmmentioning

confidence: 99%

A Modified Adaptive Genetic Algorithm for Multi-product Multi-period Inventory Routing Problem

Mahjoob¹,

Fazeli²,

Milanlouei³

et al. 2021

Preprint

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Recent developments in urbanization and e-commerce have pushed businesses to deploy efficient systems to decrease their supply chain cost. Vendor Managed Inventory (VMI) is one of the most widely used strategies to effectively manage supply chains with multiple parties. VMI implementation asks for solving the Inventory Routing Problem (IRP). This study considers a multi-product multiperiod inventory routing problem, including a supplier, set of customers, and a fleet of heterogeneous vehicles. Due to the complex nature of the IRP, we developed a Modified Adaptive Genetic Algorithm (MAGA) to solve a variety of instances efficiently. As a benchmark, we considered the results obtained by Cplex software and an efficient heuristic from the literature. Through extensive computational experiments on a set of randomly generated instances, and using different metrics, we show that our approach distinctly outperforms the other two methods.

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Green Supply Chain Network Design with Emphasis on Inventory Decisions

Cited by 2 publications

References 13 publications

Designing a Green Supply Chain Transportation System for an Automotive Company Based On Bi-Objective Optimization

Designing a Green Supply Chain Transportation System for an Automotive Company Based On Bi-Objective Optimization

A Modified Adaptive Genetic Algorithm for Multi-product Multi-period Inventory Routing Problem

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