Proceedings of the 11th Annual International Conference on Industrial Engineering and Operations Management

Singapore, March 7-11, 2021

Implementation Technologies of an Advanced Cloud-based

System for Distribution Operations
Sotiris P. Gayialis, Evripidis P. Kechagias, Angeliki Deligianni, Grigorios D. Konstantakopoulos, Georgios A.
Papadopoulos
Sector of Industrial Management and Operational Research, School of Mechanical Engineering
National Technical University of Athens
Zografos, 15780, Greece
sotga@mail.ntua.gr, eurikechagias@mail.ntua.gr, aggdelig@mail.ntua.gr, gkonpoulos@mail.ntua.gr,
gpapado@mail.ntua.gr

Abstract

Today's era is characterized as the “digital transformation era”. Digital processes and information systems are used
in every aspect of social and business activity. The use of information technology over the internet is so extensive
that we interact with it daily without even recognizing it. The technological advances can offer a plethora of
improvements for the supply chain processes, especially in the field of distribution planning and execution. At the
same time, the development of advanced information systems for usage in urban freight transportation operations is
still at an early stage. The scope of this paper is to present the technological content of an advanced routing and
scheduling system for transportation and delivery of goods. The system focuses on the routing and scheduling
problem in urban areas, as city logistics have become a complex environment for companies to deliver their goods.
The presented system deals with both static and dynamic routing and scheduling problems. More specifically, the
system can create initial routing plans based on orders, available vehicles, time windows, and traffic forecasting
data. Afterward, during the execution of the plans, the system can monitor the fleet, detect deviations from the
original plans, and finally, perform rerouting operations when needed. After a brief presentation of the system’s
modules and functionality, the paper describes thoroughly the technologies used to develop the system. The
technological elements of the system are integrated into a cloud environment offering a system that is easy to
maintain and can effectively support logistics companies’ distribution activities. The system is provided as a
Software as a Service with data being maintained on a central host and processed on the cloud. Therefore, logistics
companies that decide to implement it can achieve faster, more accurate and more cost-efficient distribution
activities while ensuring better customer service.

Keywords
Routing and Scheduling, Distribution, City logistics, Software as a Service, Information System

1. Introduction
The distribution of goods is a key component of all city supply chains (Sanjay et al. 2020). Urban Freight
transportation (UFT) is the part of urban transportation that deals with the distribution of goods in cities and, over
the years, has gained significant economic importance (Rose & Martínez 2007). However, as valuable as it is for
cities, UFT is associated with a plethora of challenges since many parties are involved. For this reason, UFT should
always be considered as a complex set of activities, functions and parties (shippers, receivers, logistics service
providers and freight carriers) that all interact with each other and need to be effectively managed (Rose and
Martínez 2007; Sánchez-Díaz et al. 2017). UFT is usually carried out on the road due as freight vehicles need to
travel through complex urban networks and have direct access to pickup and delivery points. Commonly, UFT is
associated with various challenges such as area restrictions (Kin et al. 2017) and traffic congestion (Macharis and
Melo 2011) and is responsible for significantly damaging the urban environment (Kijewska et al. 2016; Russo and
Comi 2012).

It becomes clear, therefore, that despite the necessity of UFT, it has led to a major transport problem due to the way
it has been executed. For this reason, there is a need for innovative ideas concerning the implementation of software
technologies in order to achieve more effective, cleaner, and energy-efficient UFT. Technological advances can

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Proceedings of the 11th Annual International Conference on Industrial Engineering and Operations Management
Singapore, March 7-11, 2021

offer a plethora of improvements for the supply chain processes and especially those related to distribution planning
and deliveries execution. It should be noted that, until nowadays, the information systems for routing and scheduling
were locally installed on the servers of logistics companies and their main disadvantage was that they didn’t have
the ability to manage real-time data and perform big data analytics. Therefore, dynamic routing of vehicles was
impossible and it was economically unprofitable to supply logistics companies with dynamically changing order and
traffic data (Dixit and Chhabra 2015).

However, technological advances have offered the ability to revolutionize the distribution of goods in urban areas.
UFT can be aided by utilizing information systems and other appropriate technologies, designed and combined
altogether in such a way that they can effectively route and schedule the deliveries of logistics companies. In order
to implement such a system, various technologies, such as development platform frameworks, cloud computing
services, databases, communication protocols, web services and application programming interfaces (APIs) are
needed to be combined and effectively integrated into a single software solution. In this scope, taking into account
the challenges of UFT and the need for real-time data management, our team developed, as part of a research
project, a cloud-based system for effective and efficient urban freight distributions. The objective of this paper is to
present the technologies used for developing the aforementioned system after firstly briefly demonstrating its
functionality.

It should be noted that, over the last few years, the way of delivering information systems has shifted from the use
of on-premise hardware and local servers to cloud-based solutions. One of the most popular new software
distribution models is the Software as a Service (SaaS) model in which the software is licensed on a subscription
basis while being hosted centrally and customers gain access through the Cloud. This way of offering software
solutions vastly differs from the on-premise software distribution model that was commonly used in the past
(Boillat and Legner 2013; Kepes and Subramanian 2020). Via the SaaS distribution model, the software is made
available to the customer through the cloud and can be accessed from any device and in any place as long as there is
an active internet connection. The charges of this model are only related to licensing fees and can be customized
according to the needs of customers (Churakova and Mikhramova 2020; Mel and Timothy 2020). SaaS has gained
increased popularity as a software distribution model, as it eliminates the need for high initial setup costs as well as
continuous maintenance and upgrade costs. This has contributed to its frequent use in Small and Medium
Enterprises (SMEs), while also Large Enterprises (LE) have started considering it as a viable alternative to the
existing solutions they use. After all, in both cases, the on-premise needed computational power, is extremely
reduced (Churakova and Mikhramova 2020).

This is why, after evaluating alternatives, it was decided that the cloud system for the distribution of goods in urban
areas should be offered to end-users as a Software as a Service. However, such an implementation also requires the
use of specific technologies for the development of the software. These technologies include the development
platform framework, the cloud computing services, the web services, the application programming interfaces, the
communication protocols and the databases. In Section 2 of this paper, the functionality and the modules of the
advanced routing and scheduling system for urban freight transportation are briefly presented. In Section 3, the
integrated technological solutions and their use in the developed system are thoroughly analyzed. Finally, in Section
4 the conclusions, as well as the next steps of the research, are discussed.

2. System’s Modules and Functionality

2.1 System’s Architectural Design and Sub-Systems

The created software solution is based on the concept and methodological approach of Gayialis et al. (2018). This
approach included a combination of the functions of different subsystems/modules and their interaction in order to
create a fully operable system. As already mentioned, the system can be provided by the software company to
logistics companies/customers using the Software as a Service (SaaS) distribution model. Since the system is offered
as a SaaS, it can be also considered as a distributed system. The basic principle that characterizes distributed systems
is their service-oriented architecture (SOA), through which they are divided into smaller subsystems that perform
individual functions, with all of them eventually getting grouped together to form an interoperable service (Niknejad
et al. 2019).

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Singapore, March 7-11, 2021

When gaining access to the system’s services, the logistics company can send details of the orders to be planned
(delivery points, delivery times, time windows) and the available fleet data (drivers, vehicles, capacity). The system
can then combine the above orders and fleet data with historical traffic data and by statistically estimating road
traffic, eventually, create an initial deliveries plan. This plan returns to the logistics company and ends up in the
navigation devices within the company's vehicles. After this phase is concluded, the distribution activities of the
logistics company can begin. However, during the execution of deliveries, the logistics company may need to
modify the route of vehicles. These modifications may happen due to cancellations of orders, changes in time
windows, mechanical damages to the vehicles as well as unexpected out-of-corporate events such as extreme traffic
congestion or weather conditions that may occur during the execution of deliveries. In such cases, if necessary, the
system implements rerouting tasks and updates the navigation devices within the company's vehicles with the route
modifications based on the changed delivery plans. Therefore, as seen in Figure 1, the architecture of the system
consists of two basic subsystems, the routing and scheduling subsystem and the data processing subsystem. Each
subsystem includes a set of modules as presented in Figure 1 and described in the next section (section 2.2) of the
paper. More details about the algorithms used in the system can be found in Kechagias et al. (2019) and
Konstantakopoulos et al. (2020). Description of the methodological approach and the development phase of the
system can be also found within the work of Gayialis et al. (2018) and Kechagias et al. (2020a; 2020b).

Routing and Data Processing

Scheduling Subsystem Subsystem
Traffic Data Processing
Traffic Forecasting Module Module

Static Routing & Scheduling Geographical Information

Decision Module Module

Dynamic Routing & Scheduling

Deliveries and Routing
Decision Module
Data Processing
Monitoring Module Module

Vehicle Logistics Company’s

Interfaces Interfaces

Figure 1: System’s Modules and Integration

2.1 The Routing and Scheduling Subsystem

The routing and scheduling subsystem includes four modules and allows interactions between the navigation devices
on vehicles and the data processing subsystem. The modules of the subsystem are the:
• Traffic Forecasting Module
• Static Routing and Scheduling Decision Module
• Dynamic Routing and Scheduling Decision Module
• Monitoring Module

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Proceedings of the 11th Annual International Conference on Industrial Engineering and Operations Management
Singapore, March 7-11, 2021

The traffic forecasting is performed by the traffic forecasting module of the routing and scheduling subsystem. The
purpose of this module is to collect historical traffic data and generate a traffic forecast in order to optimize the
initial routing plan of the systems’ algorithm.

All routing and scheduling data (orders, vehicles and depots) are sent to the decision module for static routing and
scheduling. Initially, a statistical estimate of the traffic is performed, and then the initial deliveries plan is generated.
The creation of this routing plan is the result of the use of an algorithm that solves the Vehicle Routing Problem with
Time Window Limitations (VRPTW). The algorithm’s objective function aims to minimize the total deliveries cost
according to various constraints. After the routing is concluded, routing plans appear both on the interfaces of the
vehicles’ navigation devices, and on the logistics company’s main interface.

In the routing and scheduling subsystem, there is also the 2nd decision module for dynamic routing and scheduling.
This module continuously detects the new information that is received. Depending on the arriving data and by using
an algorithm that solves the Dynamic Vehicle Routing Problem with Time Windows (DVRPTW), the module
implements either re-routing of orders or modifications of delivery schedules. Eventually, again all changes appear
on the navigation devices on vehicles and on the logistics company’s main interface.

Finally, the monitoring module of the routing and scheduling subsystem offers the visualization of the routes
produced by the vehicle routing modules (static and dynamic). Through this module, the routes are sent either to
vehicle devices or to the company's information systems for further analysis . This module can also be used for real-
time tracking of vehicle routes. Finally, through this module, the various events, extraordinary or not, that take
place during transportation operations and are related to the execution of the itineraries and the deliveries, are
recorded.

2.2 The Data Processing Subsystem

The data processing subsystem is responsible for data management and processing in order to calculate the static and
dynamic plans for the deliveries. The three modules of the subsystem are the:
• Geographical Information Module
• Deliveries and Routing Data Processing Module
• Traffic Data Processing Module

The geographical information module consists of spatial data analysis tools. These tools are able to present the real
world at various thematic levels and can also exhibit patterns and relationships between geographic data in order to
explore problems, in our case mainly road problems, but are not limited to them. The geographical information
module is designed to receive, analyze, interpret, and store data from Global Positioning Systems (GPS) and is
integrated with commercial cartographic software for calculations and mapping.

The deliveries and routing data processing module manages the system’s database. Indicative data included in this
module are static deliveries and routing data, such as deliveries data (customers' name, order quantity, shipping
address, cost, dates, payment methods etc.), fleet data (quantity, availability and personal details of drivers and the
quantity and capacity of either its private vehicles or the rented etc.), scheduling restrictions (limitations, created by
social, technical, environmental, legal and economic factors), distribution times forecasts (historical data from
previous distributions and future predetermined factors) and time windows (defined time slots during which
distribution is allowed). However, since the scheduling of deliveries suffers from uncertainty, it is also necessary to
gather dynamically changing data, such as order modifications, time window modifications and fleet problems.

The traffic data processing module includes the management of both static and dynamic traffic congestion data.
Static traffic data is provided by map providers while traffic forecasting can be performed either by map providers
or by the system’s algorithms at the traffic data forecasting module. In this way, it is possible to forecast road traffic
as well as transportation times from one point to another. In addition, the data provider also offers dynamic (real-
time) traffic data coming from all mobile devices in the road network that have active location services. Based on
the dynamic data, the module can accurately calculate the speed at which the vehicles move in the road network.

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Proceedings of the 11th Annual International Conference on Industrial Engineering and Operations Management
Singapore, March 7-11, 2021

3. Implementation Technologies of the Advanced System

3.1 Summary of Implementation Technologies

As already mentioned, the system is provided to logistics companies/customers through the Software as a Service
distribution model. The system was developed as a Platform as a Service (PaaS), using a development platform
framework offered by a cloud computing service. Web services and APIs were used for the management of data
exchanged between the central host of the software provider and the cloud platform as well as between the
information systems of the users (logistics companies) and the cloud platform, using a communication protocol.
Successful communication of the host, the subsystems, and the web services required the use of such an appropriate
communication protocol. Finally, a database was also needed for the management and storage of the various data.

The technologies and the technical elements of the system are shown in Figure 2. Additionally, Table 1 presents the
specific implemented solutions and the functions of the system that they enable, which are further explained in the
next section of the paper.

(CP) (CP)

Figure 2: Technologies and Technical Elements of the System

Table 1: Implemented Technological Solutions & Usage in the System’s Functions

Technical Aspect of the System Solution Implemented Usage in System’s Functions
Guidance for writing and integrating
Development Platform
Microsoft .NET algorithms and web services into the
Framework
system
Receiving all needed services from the
geographic and traffic data provider and
Used the ones offered by
sending back data for geographic
Web Services & APIs the geographic and traffic
calculations.
data provider
Receiving user’s data for deliveries and
sending back the delivery plans.
REpresentational
Communication of software host, users,
Communication Protocol State Transfer Protocol
subsystems, web services and APIs
(REST)
Storage and management of all needed
Database Oracle Database
data
Developing the system and providing all
Cloud Computing Service Microsoft Azure
necessary tools

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Proceedings of the 11th Annual International Conference on Industrial Engineering and Operations Management
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3.2 Development Platform Framework

The development platform framework is a library of various integrated technologies and serves as a basis for
developing software solutions. The development platform that is created based on the selected framework is
essentially the environment in which a piece of software is executed and it can have the form of hardware,
operational systems or even web browsers. The development platform contains a back-end and a front-end. The
back-end is used to launch the operating system's programs in response to front-end’s requests. The implementation
of the development platform depends on the needs and the objectives of the software development company (Miller
2003; Vawter and Roman 2020). The development platform provides all tools that are necessary for the operation of
the cloud system. The system is developed as a Platform as a Service, allowing developers to create their own
applications on an existing platform base with the aid of a plethora of advanced tools.

The two most common platform frameworks for developing applications and web services are Microsoft .Net
(commonly found as .Net) and the Java Platform Enterprise Edition (J2EE). Both of these frameworks were born
from existing application server technologies (Cobus et al. 2020; Vawter and Roman 2020). For the development of
the system, it was decided to use the .NET framework. This framework shows many similarities with the Microsoft
Windows operating system and is widely used for business application development. An important advantage of this
framework is that developers can more easily create software solutions due to its linguistic neutrality and its simple
programming model. Additionally, all vehicle routing and traffic forecasting algorithms, used in the system, were
coded in Python, a programming language that can easily “talk” to.NET through its bridges. Last but not least, .NET
is also integrated into the cloud computing platform, Microsoft Azure that was used as a service for the development
of the system and is analyzed in Section 3.6.

The user interfaces for both the logistics companies and the drivers, that consist the front end of the system, were
also created based on the .NET framework. The logistics companies’ user interface includes the home page and two
additional pages, the deliveries and the assets tabs. In the first tab, users can upload the orders needed to be routed,
view the orders and the delivery point on map, and perform the vehicle routing and deliveries scheduling tasks. In
the second tab, the users can view and modify data related to their assets. More specifically, they can manage the
locations of the hubs, the types of vehicles, the specific vehicles that are available for deliveries, the drivers and
finally the shifts of the drivers.

3.3 Web Services and APIs

Web services are a subset of web applications, that can be used as independent applications and are published on
the Internet. Software development companies can use them as parts of the applications they develop (Curbera et al.
2001; Gottschalk et al. 2018). They can be hosted by any application offering open access and can be used by any
client who understands JSON (JavaScript Object Notation) or XML (Extensible Markup Language). Finally, they
support the HTTP protocol (Hypertext Transfer Protocol) for URL usage, request/response headers, caching,
versions, content formats. Web services can be considered as a subset of application programming interfaces (APIs)
that require connection to the internet. APIs are interfaces that can be utilized in order to create software solutions
that interact with already developed applications. It should be also noted that web services require the use of a
communication protocol, while APIs are protocol agnostic (Souza et al. 2004).

The web services and APIs were used for the static vehicle routing and scheduling of deliveries to:
• receive the geographic data provider’s data
• calculate the distance and transit times matrices
• show the created delivery schedules and delivery points on the map
• send the created delivery schedules to the drivers’ user interfaces
• receive deliveries, depots and vehicles data from the user
• send the created delivery schedules and plans to the logistic company’s system
• send the created delivery schedule to the drivers’ portable devices

The web services and APIs were also used for the dynamic vehicle routing and scheduling of deliveries to:

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Proceedings of the 11th Annual International Conference on Industrial Engineering and Operations Management
Singapore, March 7-11, 2021

• receive the geographic data provider’s data

• receive the traffic data provider’s data for real-time traffic forecasting
• recalculate the distance and transit times matrices
• show the created delivery schedules and delivery points on map
• receive delivery exceptions or problems during the execution of the route
• send the recalculated routes and schedules to the logistic company’s system
• send the recalculated delivery schedule to the drivers’ portable devices

3.4 Communication Protocol

In order to communicate and exchange data between the host, the modules of the system, or even in cases where
communication with web services and APIs is needed, a communication protocol is necessary (Lo Iacono et al.
2019). The communications are enabled either by using the Simple Object Access Protocol (SOAP) or the
REpresentational State Transfer protocol (REST) (Lo Iacono et al. 2019; Potti 2011). For the system’s development,
it was decided to use the REST protocol as it is the most popular protocol used for web applications due to its
flexibility and performance. Additionally, this protocol offers fast response times, a fact that is critical for all real-
time functions of the system. Finally, the REST protocol was selected over the SOAP one as it offers live
interactions with maps APIs.

3.5 Database

A database is a collection of data or organized information (Berg et al. 2012). There are two main categories of
databases used in software development, Structured Query Language (SQL) databases and Not only SQL (NoSQL)
databases. These two types of databased can be mainly distinguished by the existence or not of relationships
between the databases’ tables (Berg et al. 2012). The most common SQL databases are MS Access, SQLite,
MySQL, SQL Server and Oracle Database (Bassil 2012), and the most common NoSQL database is MongoDB
(Berg et al. 2012).

For the development of the system, it was decided to use SQL databases as the system needs to continuously
manage the relationships between all stored data. Selecting the appropriate SQL database included the analysis of
various commercially available products. Microsoft Access Services was one of those alternatives but wasn’t
powerful enough and was found to be discontinued by Microsoft on 2018. SQLite is a very light product (less than
500Kb) compared to other solutions but is also unable to withstand the level of data management the system
requires. As for the free open-source solution MySQL, it was found that it cannot provide the security and
scalability that the system needs. The database that was finally selected for the system was Oracle Database as it can
manage dynamic data and also offers great performance and reliability.

3.6 Cloud Computing Service

As seen in Section 2 of this paper, the routing and scheduling subsystem is the core element of the developed system
and operates in the cloud. For its development, a state-of-the-art cloud computing service offered by the providers of
cloud computing was needed. The system could be developed either as a Platform as a Service (PaaS) or as an
Infrastructure as a Service. PaaS offers the ability to develop new software solutions on an existing software base or
development environment. IaaS, on the other hand, enables the use of standard cloud computing services. For the
development of the system, PaaS was found to be the solution that better serves our needs. The software solution
selected for the development of the system was Microsoft Azure, which provides all the necessary tools for the
integration of algorithms, web services and APIs. Moreover, Microsoft Azure was selected as it can easily
communicate with REST APIs and offers.NET as an integrated framework. Finally, Microsoft Azure cloud
computing service facilitates the distribution of the system as a Software as a Service (SaaS).

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Proceedings of the 11th Annual International Conference on Industrial Engineering and Operations Management
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4. Conclusions
As it becomes clear, today more than ever, the use of cloud-based software solutions can offer a plethora of benefits
for logistics companies and most notably can facilitate their distribution services. In this scope, the presented cloud-
based system could aid logistics companies in order to achieve more effective, cost-efficient and environmentally
friendly order deliveries to their customers. More specifically, the convenience, reliability and security provided by
the system, can lead logistics companies to better control their processes, increase their efficiency while also
ensuring the quality of their services/products. All these benefits are vital for logistics companies operating in
today’s competitive environment. The technologies used for the development and the interconnection of the system
and its individual subsystems are the key part for the successful provision of the software solution. The technologies
needed for the development of the system included the development platform framework, the cloud computing
service, the web services, the application programming interfaces, the communication protocols and the database.

The implementation of these technologies enabled the development of an advanced cloud-based information system
for vehicle routing and scheduling, especially in urban areas. The main advantage of the developed system and the
implemented technologies is that it can be easily applied in every logistic company, as a cloud service, while it deals
with critical constraints of the routing and scheduling problem, like traffic congestions and exceptions during the
execution of the schedules. The developed system has been already tested and its operation has been simulated using
data from real-life logistics companies. The next goal of our research is to validate the system with the delivery
operations of specific logistics companies in real-life conditions. The results of the various performed tests and
system validation will be then evaluated and any necessary improvements will be implemented to the system, in
order to be ready for exploitation by the logistics sector.

Acknowledgements
The present work is co-funded by the European Union and Greek national funds through the Operational Program
"Competitiveness, Entrepreneurship and Innovation" (EPAnEK), under the call “RESEARCH-CREATE-
INNOVATE” (project code: T2EDK-00508 and Acronym: COUNTERBLOCK).

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Biographies

Sotiris P. Gayialis has a Diploma in Mechanical Engineering (1997) and a PhD (2008) in Business Process
Management and Supply Chain Management from the National Technical University of Athens (NTUA), Greece.
He is currently a Teaching and Research Associate of Supply Chain Management Processes in the Sector of

© IEOM Society International 2093

Proceedings of the 11th Annual International Conference on Industrial Engineering and Operations Management
Singapore, March 7-11, 2021

Industrial Management & Operations Research at NTUA. He is also an adjunct faculty member of Hellenic Open
University. His academic interests are Logistics and Supply Chain Management, Business Process Management,
Business Process Improvement, Operations Management and Management Information Systems. He has a twenty
year experience in research projects and management consulting. He has participated in a large number of business
process improvement and reengineering projects, enabled by IT technology. He has published more than eighty
papers in journals, chapters for books and international conferences.

Evripidis P. Kechagias is currently a PhD student at the National Technical University (NTUA) of Athens, School
of Mechanical Engineering, Sector of Industrial Management and Operational Research. He has studied Mechanical
and Industrial Engineering at NTUA (2017) and presented a diploma thesis entitled “Business process management
integrated with risk management in the construction industry” that was awarded the honors degree. He also owns a
MSc in the field of Technoeconomic studies. His academic interests revolve around the areas of Information
Technologies, Business Process Modeling, Analysis and Management, Operational Research, Information System
Management, Knowledge Management, Project Management, Industrial Management, Enterprise Resource Planning
Systems, Logistics and Supply Chain Management, Production Decisions and Planning. He has published academic
and conference papers on these areas.

Angeliki Deligianni is currently a PhD student at the National Technical University of Athens (NTUA), in the
School of Mechanical Engineering. She holds a Diploma in Mechanical Engineering, with expertise in Industrial
Management and Operational Research, and presented a diploma thesis entitled “Software Development
Technologies for the Implementation of Urban Freight Transport Systems”. Her academic interests revolve around
the areas of Risk Management, Management Information Systems, Project Management and Supply Chain
Management.

Grigorios D. Konstantakopoulos is currently a PhD student at the National Technical University of Athens
(NTUA), in School of Mechanical Engineering. He has studied Mechanical Engineering at NTUA (2017), with
specialization in Industrial Management and Operational Research, and presented a diploma thesis entitled “Vehicle
Routing Systems for Urban Freight Transportation: Field Review and Specifications”. His academic interests
revolve around the areas of Vehicle Routing Problem, Operational Research, Business Process Management,
Logistics and Supply Chain Management. He has published academic and conference papers on these areas.

Georgios A. Papadopoulos is a teaching Staff at the School of Mechanical Engineering NTUA Sector of Industrial
Management & Operations Research and deals with educational, research and administrative tasks. He has studied
Mechanical and Industrial Engineering at NTUA (1994) and followed post-graduate studies at the university of
wales, Cardiff business school, UK, obtaining a Master of Business Administration (MBA) (1996). He also obtained
a PhD at the National Technical University of Athens, School of Mechanical Engineering, Sector of Industrial
Management and Operational Research in the area of Production Planning Decisions (2009). He has participated in
many projects and publications in the areas of Production Decisions, Production Planning and Control Systems,
Information Systems, Web Design and Development, Application Development.

© IEOM Society International 2094