Vehicle routing problem with cross-docking in a sustainable supply chain for perishable products

محورهای موضوعی : Supply chain management and logistics

Fatemeh Shahrabi ¹ , Mohammad Mahdi Nasiri ² , Mohammad Javad Mirzapour ³ , Negin Esmaeelpour ⁴

1 - School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran
2 - School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran
3 - Department of Industrial EngineeringIndustrial Production, amirkabir university of technology, tehran iran.
4 - School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran

تاریخ دریافت : 1403/05/13 تاریخ پذیرش : 1403/08/01 تاریخ انتشار : 1403/08/01

کلید واژه: Sustainable vehicle routing problem, Cross-docking, Freshness, Job satisfaction, Genetic algorithm, Social responsibility,

چکیده مقاله :

Today's transportation systems, which largely rely on the combustion of fossil fuels, play a significant role in contributing to energy-related greenhouse gas (GHG) emissions, thereby raising serious concerns about sustainability. As awareness of environmental issues grows, incorporating sustainable practices into logistics, particularly in cross-dock scheduling, is becoming increasingly vital. This paper introduces a sustainable vehicle routing problem (VRP) that integrates cross-docking to enhance decision-making within logistics systems. Beyond purely economic considerations, it emphasizes critical aspects like environmental impacts, notably CO2 emissions, and social factors such as equity among drivers and overall customer satisfaction. To tackle these complex challenges, a metaheuristic approach blending Genetic Algorithms (GA) with mixed integer programming (MIP) is proposed as an effective solution strategy. The method's efficacy is validated through various instances of differing sizes, revealing that the GA yields results with minimal deviation from optimal fitness values in smaller instances. Additionally, a comprehensive real case study is conducted to showcase the model's applicability in practical scenarios and finally, some suggestions for further researches are given. This study not only illustrates the operational benefits of the proposed approach but also underscores the importance of sustainable logistics in mitigating environmental impacts while fostering social equity and enhancing customer experience.

چکیده انگلیسی:

Today's transportation systems, which largely rely on the combustion of fossil fuels, play a significant role in contributing to energy-related greenhouse gas (GHG) emissions, thereby raising serious concerns about sustainability. As awareness of environmental issues grows, incorporating sustainable practices into logistics, particularly in cross-dock scheduling, is becoming increasingly vital. This paper introduces a sustainable vehicle routing problem (VRP) that integrates cross-docking to enhance decision-making within logistics systems. Beyond purely economic considerations, it emphasizes critical aspects like environmental impacts, notably CO2 emissions, and social factors such as equity among drivers and overall customer satisfaction. To tackle these complex challenges, a metaheuristic approach blending Genetic Algorithms (GA) with mixed integer programming (MIP) is proposed as an effective solution strategy. The method's efficacy is validated through various instances of differing sizes, revealing that the GA yields results with minimal deviation from optimal fitness values in smaller instances. Additionally, a comprehensive real case study is conducted to showcase the model's applicability in practical scenarios and finally, some suggestions for further researches are given. This study not only illustrates the operational benefits of the proposed approach but also underscores the importance of sustainable logistics in mitigating environmental impacts while fostering social equity and enhancing customer experience.

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