Sustainable Supply Chain Management of COVID-19 Vaccines for

Vaccination Delivery based on Routing Algorithms

THEODOROS ANAGNOSTOPOULOS1, MICHAIL PLOUMIS2, ALKINOOS PSARRAS1,

FAIDON KOMISOPOULOS1, IOANNIS SALMON1, KLIMIS NTALIANIS1,

S. R. JINO RAMSON3

University of West Attica,

12243 Athens,

Abstract: - Covid-19 pandemic has changed daily life in the city of Athens where vaccines are exploited with

supply chain technology potentiality. Vaccines are tracked at the city’s airport till their delivery to vaccination

centers. Due to the sensitivity of vaccines to the warm climate inherent in the city, delivery is assigned to a fleet

of trucks. Specifically, two use cases, i.e., UC-I and UC-II, are proposed, which are based on global and local

routing algorithms to exploit trucks’ load COVID-19 vaccine delivery from the airport and transport it to

regards to the adopted use cases’ routing algorithms.

Received: May 15, 2023. Revised: October 23, 2023. Accepted: November 7, 2023. Published: November 17, 2023.

This Covid-19 era changed rapidly the social

interaction of citizens in smart cities, [1]. Although,

smart cities are the future of earth habitation,

according to the Cities 2.0 paradigm, where 67

and local scheduling, and global and local routing,

are incorporated to make feasible the establishment

of smart cities due to high-quality technological

advancements in the area of smart devices, such as

sensors and actuators, and remake the way we make

things, [3]. However, technology by itself is not

adequate to preserve the healthcare and safety of the

smart cities’ population, [4]. Covid-19 emerged with

new challenges, which should be undertaken to face

current threatening reality, [5]. Lockdown, mask

certain schedule, [7]. In the case of Greece, COVID-

19 vaccines have entered the country through the

smart city of Athens airport. When airplane flights

which uses trucks to collect vaccines from the

airport’s warehouse and distribute them to

vaccination centers in the city of Athens.

To further analyze the significance of the

examined research area, in, [8], the authors perform

an analysis focusing on the impact relational

governance has on designing performance

improvements in the area of cultural intelligence of

smart cities. Such a system is based on Structural

Equation Modelling (SEM), which aims to provide

supplier relationship system, that focuses on social

performance improvement. Such a system performs

an extensive survey of adequate methods aiming to

face social performance. Results indicate that

fundamental elements of commitment and relational

governance should be combined to produce a viable

green ecosystem in smart cities.

It should be noted that Athens is a smart city in

Greece based on research proposed in, [10], where it

is presented a system, that incorporates sustainable

planning for the smart city of Athens focusing on

the economic role required to support an integrated

strategy for a green environment.

In this paper, we focus on the green and

sustainable supply chain management technology of

collecting COVID-19 vaccine stock from the airport

and delivering it with the incorporation of trucks to

vaccination centers in the area of the smart city of

Athens Greece. Such a system focuses mainly on the

adoption of sustainable supply chain management to

quality of life as well as the technical maturity of the

adopted infrastructural operations. Since vaccines

order new vaccines on time from the system. There

is proposed a system, that faces the population needs

to be vaccinated. Concretely, certain use cases are

performed, namely UC-I and UC-II, to treat the

vaccination distribution process. Supply chain

technology is assessed by incorporating certain

evaluation parameters for both use cases, such as

spatial and temporal distance, fuel consumption,

cost of routes in Euros, and efficiency of sustainable

its requirements for an integrated supply chain

management of vaccination process service.

The proposed research effort has an innovative and

methodological impact in the areas of:

The rest of the paper is structured as follows. In

Section II related work is provided. Section III

certain results. Section VII discusses the observed

results, while Section VIII concludes the paper and

proposes research work for an upcoming future

pandemic.

business (B2B) and business-to-customer (B2C)

channels regarding novel approaches in supporting

where the goal of the proposed solution is the

minimization of total costs without loss of the

provided sustainable healthcare service. A green and

sustainable platform, which delivers COVID-19

vaccines from stock by exploiting electric vehicle

technology is proposed in, [18]. Such a system uses

effectively the available capacity of electric vehicles

to perform accurate online distribution of the

vaccines in the city. A sustainable system is

proposed in, [19], where there is analyzed a facility

Intuitively, the adopted solution’s main effort is to

respect the quality of life thus providing green

approaches in facing the coronavirus. However,

such systems might have more expensive operations

than others.

that uses blockchain solutions incorporating smart

procurement contracts to automate the organization

research effort analyze a routing algorithm, which is

able to serve the vaccination needs of a smart city.

Specifically, it uses a fleet of UAVs within a certain

range and payload constraints to deliver covid-19

vaccine in real time. According to, [28], the authors

present a system where it is achieved an effective

vaccination process in smart cities based on a

proposed routing algorithm. Such a system focuses

on routing simulation analysis to deliver COVID-19

vaccines to certain vaccination centers. In, [29], the

system for facing smart cities’ healthcare

requirements. Such a system is able to treat covid-19

vaccination process under a distributed and robust

evolutionary routing algorithm.

Solutions adopted in this section focus mainly

on technical safety and soundness to treat the

coronavirus problem in smart cities. Intuitively,

such systems are designed to achieve efficient

operation expenses and a wider area of applications

within cities’ infrastructure.

Modeling the barriers of a transparent supply chain

for a COVID-19 research scenario is proposed in,

transparent to the end users. According to, [34], the

authors discuss the impact of supply chain

disruption management on SMEs' performance with

regard to covid-19 pandemic in India from the

perspective of developing countries' survivability.

The consequences of supply chain practices on

flexibility during covid-19 pandemic with risk

analysis and management options are studied in,

[35]. Of particular research interest is the supply

chain management in several economic sectors in

population from the pandemic. In, [37], the authors

have designed a system, which is able to provide a

vaccine supply chain to citizens according to their

needs. They have taken into consideration the

fragrant nature of COVID-19 vaccines and have

performed risk management analysis to provide

vaccines in cool temperatures thus avoiding loss of

healthcare equipment. In, [38], the authors take into

consideration the sensitivity of COVID-19 vaccines

and propose a local simulation to improve the

developing countries as a supply chain and stock

operations problem. The study encodes certain types

of vaccines according to their current temperature

and distributes them in an efficient way, thus

eliminating the loss of vaccines due to high

temperatures. According to, [40], the authors in their

research effort analyze efficient logistics and supply

chain management operations during the period of

the coronavirus pandemic. They are also discussing

how the research community can learn lessons from

time-available vaccines to certain vaccination

centers.

In this paper, there is an intention to design a

supply chain global and local routing system, which

will exploit the strengths of the available research

efforts while simultaneously avoiding their

weaknesses. The proposed system exploits related

work systems' potentiality to maximize strengths

and eliminate weaknesses of the addressed research

efforts. Specifically, we propose a green supply

chain system architecture, which faces the

population that needs to be vaccinated. Concretely,

emergency reactions, which affect the quality of

technical soundness based on the adopted

infrastructure. Certain use cases are introduced,

namely UC-I and UC-II, to evaluate the proposed

vaccination delivery process. Specifically,

sustainable supply chain technology is assessed by

incorporating certain evaluation parameters for both

use cases, such as spatial and temporal distance, fuel

consumption, and cost of routes in Euros. In

addition, adopted parameters are input to the

system parameters. Subsequently, findings are

provided to support third parties, such as the smart

city of Athens Ministry of Health, and decision

support headquarters’ control center. Concretely, the

control center is responsible for assessing the

observed results and deciding which supply chain

use case and proposed algorithm to adapt to face the

coronavirus pandemic.

since vaccines need to be preserved in low

temperatures to avoid loss. The smart city of Athens

temperatures of vaccines during the distribution

process. Vaccination centers have adequate storage

areas to stock delivered vaccines. The distribution of

vaccination centers in the smart city of Athens is

presented in Figure 1.

COVID-19 vaccines to be aware of the amount of

vaccines that should be ordered from the green

supply chain architecture for use by certain city

populations. In addition, vaccination centers take

management to face COVID-19 as a social health

threat that needs urgent technical treatment. Such a

proposed approach is designed to provide citizens an

adequate well-being status quo as well as technical

operational efficiency during their daily social

interaction schedule in a smart city.

fleet of trucks to support such a service in the smart

city of Athens to provide a green footprint in the

compared to UC-I with respect to the CO2 emissions

produced in kilograms. It is proved that UC-II is

more efficient than UC-I since UC-II produces less

carbon dioxide emissions than UC-I (See Section 6).

Concretely, shortest routes technology is adopted,

which serves the nearest vaccination centers like

these that are near the airport. In addition, such

routes follow a multi-hop approach to serve distant

points after delivering vaccines to the shortest ones.

Actually, the proposed algorithms are implementing

vaccination centers is performed by a dedicated

global routing algorithm for the whole coverage area

chain system architecture overview is presented in

Figure 2.

proposed use cases incorporated in the research

denotes the Athens airport where vaccines are

imported from abroad countries and has value 1

airport. Specifically, in the case of UC-I, we have

where vaccines are delivered by trucks and has a

value of 1 smart city. The number of trucks assigned

to deliver vaccines from the airport to the whole city

number of vaccination centers is defined with the

is defined within the interval [10, 60] kilometers,

where the nearest vaccination center in the city has a

distance of 10 kilometers from the airport, while the

most distant vaccination center in Athens has

is assigned to the temporal distance a truck requires

to transport vaccines to vaccination centers in the

city, such parameter takes values with the interval

interval of [3.5532, 8.2908] kilograms, where diesel

oil is considered to produce CO2 emissions of 0.846

kilograms per 1 litter of fuel.

centers. Vaccines transported by trucks per sector

vaccination centers per sector is defined with the

interval [10, 20] kilometers, where the nearest

is presented in Table 3, while the Shortest path UC-I

the supported local routing algorithm are relevant to

the needs of certain city sectors. Such sectors’

of the UC-II algorithm is defined to be 󰇛󰇜, since

a route assignment is performed to each smart city

truck per selected sector, which faces online routing

inefficiencies during local algorithm execution. UC-

II local routing algorithm is presented in Table 5,

while the Shortest path UC-II is presented in Table

6.

algorithm is used as the main model of routing in

both adopted use cases in the current research effort.

Such a modification has been performed to extend

spatiotemporal trajectory. A given trajectory serves

subsequently each vaccination center starting from

the nearest one up to the furthest of them based on

certain inferred route vectors computed per cycle of

the model’s execution.

Fig. 6: Total cost spent in Euros

Source: Authors

is the capital city of Greece, which is Athens. The

data used for the experiments are synthetic.

Specifically, there are used real unclassified data

provided online by the smart city of Athens, [43].

Such data are the number of vaccination centers, the

number of vaccines, and the number of trucks.

Based on these real data we implemented a

simulation environment to test the proposed global

and local routing algorithms. Synthetic data are

formed by using real data as ground truth

information for our simulations. Specifically,

visualized as shown in Figure 1. Consequently, the

sum of the vaccines required to be delivered to the

whole city where divided by the number of

vaccination centers as presented in Table 1 and

Table 2 for UC-I and UC-II, respectively.

Subsequently, vaccination centers were divided by

the number of municipalities that existed in the

whole city area thus forming the examined sectors.

Based on this information a certain fleet of trucks is

assigned to the whole smart city for UC-I while a set

Fig. 8: Total CPU execution time required in

Source: Authors

certain Gaussian distribution white noise to observe

parameter variables of the proposed system.

Simulation algorithms are implemented in Python

release version 3.9.10, while experiments were

performed on an HP ProBook 455R G6 computer

distance required to deliver vaccines, in hours, in

both use cases. Figure 5 presents the fuel

consumption, in litters, of the local and global

algorithms. Figure 6, presents the total amount of

cost, in Euros, spent in delivering vaccines to

vaccination centers by both algorithms. Figure 7

presents the CO2 emissions produced, in kilograms,

to the smart city green and sustainable environment

for UC-I and UC-II. Figure 8, presents the total CPU

execution time required, in minutes, to observe the