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A Lagrangian relaxation algorithm and hybrid genetic algorithm-black widow optimization for perishable products supply chain with sustainable development goals consideration

  • S.I.: OR for Sustainability in Supply Chain Management
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Abstract

In this study, a location-inventory-routing problem (LIRP) for perishable products with a many-to-many network and a heterogeneous vehicle fleet is considered. Retailer demand changed in the different time periods, and decreased as a function of the lifetime of the perishable product. A lost sale due to quality loss is considered. Taking the necessary actions to limit climate change and efficient use of natural resources are some of the Sustainable Development Goals (SDGs) in the supply chain management environment (Number 12 and 13 of SDGs). The carbon dioxide (CO2) cap-and-trade mechanism is considered due to its significant contribution to the control of global warming. In this study, LIRP sought to minimize the fixed and variable transportation costs, inventory holding costs, facility opening costs, lost sales costs, and the amount of CO2 emissions. A mixed integer non-linear programming (MINLP) model is proposed and validated in general algebraic modeling system (GAMS). A Lagrangian relaxation algorithm and hybrid genetic algorithm-black widow optimization (HGABWO) are considered to solve the different problems and specify the best lower and upper bounds. Our findings showed that results of the solutions obtained from the HGABWO algorithm are better than those of the genetic algorithm (GA) and black widow optimization (BWO) algorithm. On the other hand, the time to solve the large-scale problems, using the proposed algorithms compared to the GAMS is significantly reduced. Finally, the sensitivity analysis is performed for the effect of the CO2 cap-and-trade mechanism on the problem. The sensitivity analysis results indicated that considering the CO2 cap-and-trade mechanism in the problem could reduce the transportation costs and CO2 emissions.

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  1. Department of Industrial Engineering, Faculty of Engineering, Kharazmi University, Tehran, Iran

    Seyed Hamid Reza Pasandideh, Misagh Rahbari & Yaser Sadati-Keneti

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  1. Seyed Hamid Reza Pasandideh
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All authors contributed to the study conception and design. Mathematical modeling, data collection, implementation and analysis were performed by SHRP, MR and YS-K. All authors read and approved the final manuscript.

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Correspondence to Seyed Hamid Reza Pasandideh.

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Pasandideh, S.H.R., Rahbari, M. & Sadati-Keneti, Y. A Lagrangian relaxation algorithm and hybrid genetic algorithm-black widow optimization for perishable products supply chain with sustainable development goals consideration. Ann Oper Res (2023). https://doi.org/10.1007/s10479-023-05532-x

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