Closed loop location routing supply chain network design in the end of life pharmaceutical products

Ahlaqqach, Mustapha; Benhra, Jamal; Mouatassim, Salma; Lamrani, Safia

doi:10.1080/16258312.2020.1752112

Cited by 17 publications

(7 citation statements)

References 21 publications

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“…However, the latter impacts the environment through high emission rates [80]. Consequently, increasing public attention to climate change and corporate social and societal responsibility including greenhouse gas emissions, quality of life, and job creation has led to the advent of sustainable supply chain management [81][82][83]. This work developed an integrated inventory-emission CO 2 model to reduce the costs associated with the lot size inventory while considering the carbon tax resulting from the CO 2 emissions generated by the transport of the goods under uncertain demand.…”

Section: Sustainable Lot Size Optimizationmentioning

confidence: 99%

Butterfly Algorithm for Sustainable Lot Size Optimization

Benmamoun,

Fethallah,

Ahlaqqach

et al. 2023

Sustainability

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The challenges faced by classical supply chain management affect efficiency with regard to business. Classical supply chain management is associated with high risks due to a lack of accountability and transparency. The use of optimization algorithms is considered decision-making support to improve the operations and processes in green manufacturing. This paper suggests a solution to the green lot size optimization problem using bio-inspired algorithms, specifically, the butterfly algorithm. For this, our methodology consisted of first collecting the real data, then the data were expressed with a simple function with several constraints to optimize the total costs while reducing the CO2 emission, serving as input for the butterfly algorithm BA model. The BA model was then used to find the optimal lot size that balances cost-effectiveness and sustainability. Through extensive experiments, we compared the results of BA with those of other bio-inspired algorithms, showing that BA consistently outperformed the alternatives. The contribution of this work is to provide an efficient solution to the sustainable lot-size optimization problem, thereby reducing the environmental impact and optimizing the supply chain well. Conclusions: BA has shown that it can achieve the best results compared to other existing optimization methods. It is also a valuable chainsaw tool.

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Section: Sustainable Lot Size Optimizationmentioning

confidence: 99%

Butterfly Algorithm for Sustainable Lot Size Optimization

Benmamoun,

Fethallah,

Ahlaqqach

et al. 2023

Sustainability

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“…Lastly, environmental sustainability in pharmaceutical supply chains has been investigated. Ahlaqqach et al [49] developed a closed-loop supply chain network model for pharmaceutical products that incorporates the recovery and recycling of packaging materials, promoting sustainability. Diaz et al [50] conducted a simulation-based analysis of the global pharmaceutical supply chain, exploring inventory management, transportation, and demand variability to identify areas for improvement and enhance efficiency and resilience.…”

Section: Literature Reviewmentioning

confidence: 99%

Scenario-Based Optimization of Supply Chain Performance under Demand Uncertainty

Gobachew

Haasis

2023

Sustainability

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This study presents a comprehensive supply chain performance optimization model that addresses the trade-off between supply chain cost and customer service level in the distribution network. The model incorporates both deterministic and scenario-based approaches, allowing for a more realistic representation of supply chain operations. The model is applied to a case company operating in the pharmaceutical supply chain in Ethiopia. The goal is to improve the company’s supply chain performance by optimizing various factors such as establishment costs, handling costs, transportation costs, and demand satisfaction. The study considers both financial measures (supply chain cost) and non-financial measures (customer service level) to evaluate the performance of the supply chain. The results of the study demonstrate the effectiveness of the proposed model in identifying the optimal trade-off between supply chain costs and customer service levels. By comparing the results of the model with the current situation of the case company, it is determined that the company can achieve significant cost reductions of up to 25.26% while still meeting customer demands. The model also takes into account the uncertainty in demand, providing more realistic recommendations for distribution center locations, transportation planning, and order fulfillment. The implications of using this optimization model include the potential for cost savings, improved decision-making, enhanced customer satisfaction, and, ultimately, a more successful supply chain. However, the study has some limitations, including a need for further research on other objectives and considerations, such as environmental impacts and disruptions, which could be addressed in future research directions.

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“…Lastly, Ahlaqqach et al (2020) presented a MIP model for a closed-loop supply chain network for supply and recovery of end-of-life pharmaceutical products. The authors considered time windows and inventory decisions in the multi-product, multi-echelon, and multi-period supply chain.…”

Section: Perishable Supply Chainsmentioning

confidence: 99%

Bi- and multi-objective location routing problems: classification and literature review

Tadaros

Migdalas

2022

Oper Res Int J

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The facility location problem and the vehicle routing problem are highly interdependent and critical parts of any efficient and cost-effective supply chain. The location of facilities heavily affects the design of distribution routes between the facilities and various demand nodes. Within locational analysis, the location-routing problem is a mathematical optimization problem that considers the underlying issues of vehicle routing and simultaneously optimizes the location of facilities and the design of distribution routes. Since, in real-life applications, it is common that decision-makers encounter more than one, often conflicting objectives, the problem can be stated in term of multi-objective optimization. This paper reviews 80 journal articles published in the field of bi- and multi-objective location-routing problems between 2014 and 2020. Included papers are classified based on several factors covering model assumptions and characteristics, objectives, solution approaches, and application area. For each application area, individual papers are presented and discussed. The paper concludes with remarks and suggestions for future research.

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Closed loop location routing supply chain network design in the end of life pharmaceutical products

Cited by 17 publications

References 21 publications

Butterfly Algorithm for Sustainable Lot Size Optimization

Butterfly Algorithm for Sustainable Lot Size Optimization

Scenario-Based Optimization of Supply Chain Performance under Demand Uncertainty

Bi- and multi-objective location routing problems: classification and literature review

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