Biobjective low-carbon location-routing problem for cold chain logistics: Formulation and heuristic approaches

A simulation-based analysis for effective distribution of COVID-19 vaccines: A case study in Norway

“…Therefore, the effective distribution through the last stage of the vaccine supply chain is important when large immunization coverage is expected. In this regard, several studies have been conducted for designing emergency supply chains and epidemic control supply chains ( Yang et al, 2021 , Saif and Elhedhli, 2016 , Leng et al, 2020 , Leng et al, 2020 ). Other studies on the vaccine supply chain address the associated challenges ( Privett and Gonsalvez, 2014 , Yong et al, 2020 , Dasaklis et al, 2012 , Dwivedi et al, 2018 ) and the need for collaboration among stakeholders of a vaccine supply chain ( Duijzer et al, 2018 , Dasaklis et al, 2012 , Lee and Haidari, 2017 ).…”

“…When multiple influencing factors, e.g., costs, responsiveness, etc., are considered, the MOP can be used to model and balance the trade-off among these conflicting factors. Based on these techniques, several optimization models have been formulated with the focuses on reducing the total costs ( Saif and Elhedhli, 2016 , Song et al, 2020 , Al Theeb et al, 2020 , Huai et al, 2019 , Dou et al, 2020 , Shahparvari et al, 2020 , Yang et al, 2020 ), reducing cargo damage ( Leng et al, 2020 , Dou et al, 2020 ), minimizing carbon emissions ( Leng et al, 2020 , Leng et al, 2020 , Al Theeb et al, 2020 , Zhang et al, 2019 ), and improving customer satisfaction ( Leng et al, 2020 , Yang et al, 2020 ).…”

Developing a Bi-objective Mathematical Model to Design the Fish Closed-loop Supply Chain

“…Also, Motevalli-Taher et al [26] optimized the wheat SCND considering the sustainability criteria and uncertainty. Leng et al [27] minimized the total logistics cost and vehicle and client waiting times by proposing a comprehensive low-carbon cold-chain based location-routing model. Chan et al [28] used multiobjective mixed-integer linear programming for smart food logistics systems.…”

An Improved Distribution Cost Model Considering Various Temperatures and Random Demands: A Case Study of Harbin Cold-Chain Logistics

“…Moreover, Zhang et al (2019) [22] and Leng L et al (2020) [23] found that there is little research on the cost of carbon emissions in logistics, especially in cold chain logistics, but now low-carbon logistics is more and more concerned by enterprises and scholars, and reducing carbon emissions is an inevitable trend in the logistics industry. how to cut carbon emissions and lower delivery costs are the key focuses in the cold chain logistics industry.…”

“…* ∼ (34) Formula ( 21) indicates the number of services, that is, a refrigerated vehicle serves one demand point at a time; formula (22) indicates the relationship between the route and the vehicle, that is, the number of vehicles is greater than or equal to the number of routes; formula (23) indicates that the distribution center is the starting point of the refrigerated vehicle; formula (24) and formula (25) mean that each vehicle leaves after unloading; formula (26) and formula (27) indicate that the delivery frequency is one time; formula (28) indicates the departure time constraint of the refrigerated vehicle; formula (29) means to ensure that the refrigerated vehicle must meet the customer time window; formula (30) indicates the vehicle load limit; formula (31) indicates to ensure that the customer demand satisfaction rate is met; formula (32) and ( 33) represent the 0-1 decision variable; formula (34) indicates that the customer demand obeys the random distribution F.…”