A Goal Programming Approach for Green Supply Chain Network Optimization

Yu, Hao; Solvang, Wei Deng; Solvang, Bjørn

doi:10.2991/iwama-16.2016.17

Cited by 4 publications

(6 citation statements)

References 19 publications

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“…Coskun et al [15] combined different tax systems and analyzed their impact on the GSCM. Yu et al [16], constructed three green manufacturing decision making models which are penalty and reward model, the non-government intervention model and the tax subsidy model, and discovered that the penalty and reward model is the best model to encourage Supply Chain partners to adopt GSCM practices. Ameknassi et al [17] highlighted that the product recovery and the government subsidy have a positive impact on reverse Supply Chain performance.…”

Section: Literature Review and Related Workmentioning

confidence: 99%

Multi Agent Approach for Environmental Customer Collaboration: Study Case in Automotive Spare Parts Sector

Idrissi¹,

Charkaoui²,

Echchatbi³

2021

IJSDP

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Recently, Environmental Customer collaboration has gained a considerable attention among researchers and Industrial enterprises. Many studies highlight that organizations can achieve a good performance level while considering customer collaboration and environmental regulation. However, the literature in the Green Supply Chain Management (GSCM) suggests having a more structured collaboration and information exchange process based between Supply Chain partners on new technologies. Towards this end, a hybrid approach based on Multi Agent Systems and Multi Objective Linear Programming is proposed as mean of automating and facilitating the environmental customer collaboration process. This research shows that MAS can be utilized to reduce the complexity and facilitate communication in the GSCM context. The applicability of the developed MAS approach is demonstrated using an industrial case study in the automotive spare parts sector.

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Section: Literature Review and Related Workmentioning

confidence: 99%

Multi Agent Approach for Environmental Customer Collaboration: Study Case in Automotive Spare Parts Sector

Idrissi¹,

Charkaoui²,

Echchatbi³

2021

IJSDP

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“…Ilgin and Gupta, [31]. Yu et al, [32] discussed the study of enterprises from sustainability perspective in the Artic regions of the north (especially these organizations which used supply chains) to gain insights into green supply chains. Yu et al, [32] investigated as a case study in the North Artic regions, the development of green supply chains and preservation of the organizations which adopted it.…”

Section: Introductionmentioning

confidence: 99%

“…Yu et al, [32] discussed the study of enterprises from sustainability perspective in the Artic regions of the north (especially these organizations which used supply chains) to gain insights into green supply chains. Yu et al, [32] investigated as a case study in the North Artic regions, the development of green supply chains and preservation of the organizations which adopted it. Amalnick and Saffar, [33] developed network of supply chains by considering the ambiguity involving effects of environment while focusing on decision variables minimizing environmental and economic costs.…”

Section: Introductionmentioning

confidence: 99%

“…Amalnick and Saffar, [33] developed network of supply chains by considering the ambiguity involving effects of environment while focusing on decision variables minimizing environmental and economic costs. Whereas Yu et al, [32] while studying conservation of enterprises which have adopted supply chains in the North Artic region gave as overview into the layout of the green supply chain.…”

Section: Introductionmentioning

confidence: 99%

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Multi-Objective Optimization in CLSCM : A Fuzzy Model with Practical Applications

Nowpada,

2024

Preprint

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This study introduces a novel mathematical model for multi-objective optimization in closed-loop supply chain management (CLSCM), addressing the complexities of time, quality, carbon emissions, and profit margin. Leveraging intuitionistic trapezoidal fuzzy numbers, the model effectively manages uncertainties in CLSCM. The interconnected constraints-time, quality, carbon emissions, and profit margin-shape sustainability and profitability. The model harmonizes these objectives, offering a comprehensive tool for CLSCM optimization. By accommodating vagueness with fuzzy numbers, the model enhances decision-making. Trade-offs and synergies among constraints are explored, providing insights for sustainable and financially viable CLSCM. Numerical experiments validate the model’s efficacy, demonstrating practical applicability in diverse scenarios. This research contributes a robust mathematical framework for industry practitioners, enhancing operational efficiency and sustainability in CLSCM.

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“…Coskun et al [16] combined different tax systems and incentive subsidy policies, and analyzed their impacts on GSC and green manufacturing. Yu et al [17] constructed three green manufacturing decision-making models under uncertain demand, namely, the reward and penalty mechanism model, the non-government intervention model, and the tax-subsidy mechanism model, and discovered that the reward and penalty mechanism is the best model to incentivize supply chain members to recycle and remanufacture waste products. Ameknassi et al [6] suggested that the performance of the reverse supply chain can be effectively improved by elevating the price of product recovery and government subsidy, and established a model to optimize the government subsidy and product recovery price for reverse supply chain.…”

Section: Introductionmentioning

confidence: 99%

Modeling and Simulation of a Multi-agent Green Supply Chain Management System for Retailers

Wei¹

2020

JESA

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In recent years, the agent technology has been successfully applied in supply chains, thanks to its excellent interactivity, proactivity, and autonomy. However, the existing research on multi-agent green supply chain (GSC) stops on the strategic and tactical levels, failing to implement the relevant supply chain models. To overcome the limitation, this paper designs a multi-agent GSC management system for retailers, with the aim to obtain scientific collaboration strategies among multiple agents and to make effective logistics decisions for the supply chain. Firstly, a 3-layer hierarchical evaluation index system (EIS) was established under the framework of the multi-agent GSC management system. Next, the authors modeled the supply-demand relationship and dynamic game of multi-agent GSC, and discussed the cooperation and negotiation models among multiple agents. Experimental results show that the proposed multi-agent GSC management model is highly effective. The research findings provide a reference for the application of multi-agent technology in other types of supply chain enterprises.

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A Goal Programming Approach for Green Supply Chain Network Optimization

Cited by 4 publications

References 19 publications

Multi Agent Approach for Environmental Customer Collaboration: Study Case in Automotive Spare Parts Sector

Multi Agent Approach for Environmental Customer Collaboration: Study Case in Automotive Spare Parts Sector

Multi-Objective Optimization in CLSCM : A Fuzzy Model with Practical Applications

Modeling and Simulation of a Multi-agent Green Supply Chain Management System for Retailers

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