scholarly journals A Multi-Scenario Optimization Model for Emergency Cold Chain Logistics Distribution

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Yile Ba ◽  
Chenxi Feng ◽  
Wenpeng Jia ◽  
Xin Liu ◽  
Jianwei Ren
Keyword(s):  
Optimization Model ◽  
Time Windows ◽  
Modern Society ◽  
Cold Chain ◽  
Uncertain Demand ◽  
Temperature Sensitive ◽  
Logistics Center ◽  
Logistics Distribution ◽  
Emergency Situations ◽  
Scenario Optimization

Cold chain logistics has been playing a more and more crucial role in modern society. As a special professional cold chain logistics, emergency cold chain logistics can provide quality assurance for temperature-sensitive products in emergency situations. Due to the fact that demand is uncertain in emergency situations, the cold chain logistics companies have to deal with the issue of uncertainty. However, there is no literature on the emergency cold chain logistics distribution optimization problem with uncertain demand. This research contributes to solving this problem. To deal with uncertain demand in emergency situations, an emergency cold chain logistics distribution optimization model with time windows is proposed based on scenario analysis. The objectives of the model are to minimize the total cost and shorten the delivery time simultaneously. The model can also optimize product procurement and refrigerated vehicle renting. The multi-scenario optimization model is applied to a Chinese cold chain logistics center to verify its effectiveness.

scholarly journals Route Optimization Tool (RoOT) for distribution of vaccines and health products

2021 ◽  
Vol 5 ◽  
pp. 34
Author(s):  
Zelda B. Zabinsky ◽  
Mariam Zameer ◽  
Larissa P.G. Petroianu ◽  
Mamiza M. Muteia ◽  
Aida L. Coelho
Keyword(s):  
Scheduling Algorithm ◽  
Emergency Situation ◽  
Route Optimization ◽  
Cold Chain ◽  
Temperature Sensitive ◽  
Middle Income ◽  
Routing And Scheduling ◽  
Emergency Situations ◽  
Effective Interventions ◽  
Health Products

Delivery of health products from provinces or districts to health facilities, including temperature-sensitive vaccines, is one of the most effective interventions to ensure availability of supplies and save lives in low- and middle-income countries. Currently, routes are hand drawn by logisticians that are adjusted based on vehicle availability and quantity of products. Easy-to-use supply chain tools are needed that planners can use in real-time to create or adjust routes for available vehicles and road conditions. Efficient and optimized distribution is even more critical with the COVID-19 vaccine distribution. We develop a Route Optimization Tool (RoOT) using a variant of a Vehicle Routing and Scheduling Algorithm (VeRSA) that is coded in Python, but reads and writes Excel files to make data input and using outputs easier. The tool takes into account cold chain distribution, is easy-to-use, and provides routes quickly within two minutes. RoOT can be used for routine operations or in emergency situations, such as delivery of new COVID-19 vaccine. The tool has a user-centric design with easy dropdown menus and the ability to optimize on time, risk, or combination of both. Training of logisticians in Mozambique indicate that RoOT is easy to use and provides a tool to improve planning and efficient distribution of health products, especially vaccines. We illustrate using RoOT in an emergency situation, such as a cyclone. RoOT is an open-source tool for optimal routing of health products. It provides optimized routes faster than most commercial software, and is tailored to meet the needs of government stakeholders. Currently, RoOT does not allow multi-day routes, and is designed for trips that can be completed within twenty-four hours. Areas for future development include multi-day routing and integration with mapping software to facilitate distance calculations and visualization of routes.

Research on the Distribution Route Optimization of Agricultural Product Logistics Based on Particle Swarm

2013 ◽  
Vol 790 ◽  
pp. 690-696
Author(s):  
Jun Liu ◽  
Jun Xiang ◽  
Gui Lan Zou
Keyword(s):  
Optimization Model ◽  
Time Windows ◽  
Particle Swarm ◽  
Agricultural Products ◽  
Route Optimization ◽  
Agricultural Product ◽  
Swarm Optimization ◽  
Logistics Distribution ◽  
Optimum Model ◽  
The Cost

Through an analysis of the characteristics of the Agricultural Products Logistics and its influence on the vehicle scheduling, this paper is to describe the vehicle routes whose vehicle number is uncertain and which are with time windows, to establish a distribution route optimization model which is effected by the cost and has a time limitation, to solve the model with the Compound Optimum Model Particle Swarm Optimization, and to compare it through some case. The optimization model of Agricultural Products Logistics has good practical value on reduce the cost of agricultural products logistics and improve the efficiency of logistics distribution of agricultural products.

An optimization model of cross-docking scheduling of cold chain logistics based on fuzzy time window

2021 ◽  
pp. 1-15
Author(s):  
Jie Lian
Keyword(s):  
Vehicle Routing ◽  
Optimization Model ◽  
Time Window ◽  
Cold Chain ◽  
Low Carbon ◽  
Scheduling Optimization ◽  
Logistics Distribution ◽  
Cross Docking ◽  
Fuzzy Time Window ◽  
Distribution Cost

In order to improve the distribution efficiency of cold chain logistics and reduce the distribution cost, an optimization model of cross-docking scheduling of cold chain logistics based on fuzzy time window is constructed. According to the complexity of cold chain logistics network, a multi-objective optimization model of cross-docking scheduling of cold chain logistics vehicle routing with fuzzy time window is established. In order to ensure the lowest total cost of cold chain logistics distribution and improve the overall customer satisfaction with service time, the Drosophila optimization algorithm is used to solve the model to obtain the optimal vehicle routing of cross-docking scheduling optimization of cold chain logistics. The simulation test results show that: after the application of the model, the cold chain logistics distribution time is significantly shortened, the distribution cost is significantly reduced, the damage cost is reduced, the carbon emission of vehicles is reduced, and the economic and low-carbon benefits are significantly improved, which can be used as an effective tool to solve the cross-docking scheduling optimization problem of cold chain logistics.

scholarly journals Assessment of cold chain and logistics management practices: a cross sectional study in Bundelkhand region of Madhya Pradesh

2018 ◽  
Vol 5 (12) ◽  
pp. 5143
Author(s):  
Ram K. Panika ◽  
Amarnath Gupta
Keyword(s):  
Management Practices ◽  
Cross Sectional Study ◽  
Logistics Management ◽  
Cold Chain ◽  
Temperature Sensitive ◽  
Sectional Study ◽  
Cross Sectional ◽  
Shake Test ◽  
The Status ◽  
Knowledge And Practice

Background: Immunization is one of the most effective disease prevention strategies. Potency of vaccine is dependent on effective management of cold chain system at all levels of vaccine handling. This study was carried out to assess the status of cold chain equipment and logistics management practices, Knowledge and practice of CCHs about cold chain equipment and logistics management.Methods: Cross-sectional study was conducted in all functional cold chain points of Damoh district using structured questionnaires provided by UNICEF.Results: Only 57.14% and 71% CCPs had dedicated space for dry storage and for conditioning of ice packs respectably. 50% CCPs had correct placement of ice-packs inside DFs. Functional thermometer inside every equipment was available in 86% CCPs. Twice daily temperature recording and temperature of ILRs was within normal range in 93% CCPs. Record of power failures and defrosting/cleaning in temperature log books was found in 57% and 43% CCPs. Temp log book was countersigned by facility in charge in 43% CCPs. UIP vaccines were stored within basket in 93%. Fractional IPV was stock out in 29% CCPs and in 07% CCPs OPV vials were found with not usable VVM. 86%, 72% and 64% of CCHs had knowledge on freeze/temperature sensitive vaccines, cold chain pray and, Shake test. In 79% CCPs expired/wasted vaccines were not documented in stock.Conclusions: Most of the components of cold chain and logistics management practices were satisfactory while there is a gap in other components which needs to be improved. 

Risk quantification in cold chain management: a federated learning-enabled multi-criteria decision-making methodology

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Henry Lau ◽  
Yung Po Tsang ◽  
Dilupa Nakandala ◽  
Carman K.M. Lee
Keyword(s):  
Decision Making ◽  
Evaluation System ◽  
Small And Medium Enterprises ◽  
Handling Time ◽  
Cold Chain ◽  
Pairwise Comparisons ◽  
Temperature Sensitive ◽  
Multi Criteria Decision Making ◽  
Firm Level ◽  
Content Type

PurposeIn the cold supply chain (SC), effective risk management is regarded as an essential component to address the risky and uncertain SC environment in handling time- and temperature-sensitive products. However, existing multi-criteria decision-making (MCDM) approaches greatly rely on expert opinions for pairwise comparisons. Despite the fact that machine learning models can be customised to conduct pairwise comparisons, it is difficult for small and medium enterprises (SMEs) to intelligently measure the ratings between risk criteria without sufficiently large datasets. Therefore, this paper aims at developing an enterprise-wide solution to identify and assess cold chain risks.Design/methodology/approachA novel federated learning (FL)-enabled multi-criteria risk evaluation system (FMRES) is proposed, which integrates FL and the best–worst method (BWM) to measure firm-level cold chain risks under the suggested risk hierarchical structure. The factors of technologies and equipment, operations, external environment, and personnel and organisation are considered. Furthermore, a case analysis of an e-grocery SC in Australia is conducted to examine the feasibility of the proposed approach.FindingsThroughout this study, it is found that embedding the FL mechanism into the MCDM process is effective in acquiring knowledge of pairwise comparisons from experts. A trusted federation in a cold chain network is therefore formulated to identify and assess cold SC risks in a systematic manner.Originality/valueA novel hybridisation between horizontal FL and MCDM process is explored, which enhances the autonomy of the MCDM approaches to evaluate cold chain risks under the structured hierarchy.

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