Analysis and Development: Monitoring System for Logistics Planning

This project delves into the development of a monitoring system for logistics planning and optimization, addressing the increasing demand for efficient delivery solutions driven by online shopping. It explores the limitations of current route planning methods and proposes a new system leveraging Google Maps API to provide real-time vehicle tracking, fuel consumption monitoring, and dynamic route adjustments based on traffic conditions. The project involves a comprehensive literature review of existing routing algorithms, including Dijkstra's and genetic algorithms, and compares their effectiveness. The aim is to create a system that enhances delivery efficiency, reduces costs, and improves customer satisfaction. The project emphasizes the importance of real-time data integration and the ability to adapt to unforeseen events, like accidents, to ensure optimal route planning and logistics management. The project seeks to provide stakeholders with a visual representation of vehicle locations and driving directions on Google Maps, offering a significant step forward in logistics monitoring.

MONITORING SYSTEM – IN LOGISTICS PLANNING AND OPTIMIZATION

ABSTRACT
Logistics industry has got its rampant and dynamic presence and future, especially in the
developed and developed countries, because of growing online shopping and buying. Instead the
shoppers moving around the shops, products from the shops started moving and reaching the
doorsteps of the customers. Moving goods is a mechanical process and so it should be
mechanized, so that maximum number of products is transmitted to the destination, within less
time and less cost per unit. Mechanization is further enhanced with the shortest path, between
origin or source and the destination. There are various route planning algorithms existing that
finds shortest path, however, there is a heavy need for much better and sophisticated algorithm
that suits for today’s complex traffic and road network structure. Advancement in the technology
has to be best exploited to reduce the cost and time of door delivery of products by the logistics
company and increase the profits.

Contents
MONITORING SYSTEM – IN LOGISTICS PLANNING AND OPTIMIZATION.........5
INTRODUCTION...............................................................................................................5
LITERATURE REVIEW METHODOLOGY.....................................................................7
LITERATURE REVIEW.....................................................................................................8
Logistics and Requirement..........................................................................................................8
Freight Networks Notation........................................................................................................10
Concept of Shortest Paths with Logistics Constraints...............................................................10
Algorithms for Routing Planning..............................................................................................11
Routing Planning Algorithms....................................................................................................12
Construction Algorithms............................................................................................12
Improvement Algorithms...........................................................................................12
Hybrid Algorithms.....................................................................................................13
Algorithms for Logistics............................................................................................................13
Greedy Algorithms.....................................................................................................13
DIJKSTRA ALGORITHM........................................................................................17
GENETIC ALGORITHMS.......................................................................................26
COMPARISON.........................................................................................................................29
GOOGLE MAPS API AND LOGISTICS APPLICATION.....................................................32
MONITORING SYSTEM.........................................................................................................33
Architecture...............................................................................................................34
CONCLUSION..................................................................................................................35

REFERENCES..................................................................................................................37

MONITORING SYSTEM – IN LOGISTICS PLANNING AND OPTIMIZATION
INTRODUCTION
The day to day habits of the people, like entertainment, travel have been
changed with the development of time and advancement of the science and
technology. Prominently changing habit these times, are shopping, a big transition
from the traditional and physical shopping to online shopping. Eventually, there is
an explosive growth to the online stores and distribution services have been an
added chunk to large number of traditional shops. The key and essential role hence
has been played by the logistics. The functionalities of logistics have been
appended with warehousing, packaging, traffic, warehousing, with significance of
more than providing shipping service to the customers. Hence, an optimized route
plan not only reduces the cost of the companies, but also increases the clients’
satisfaction. The new methods have also need to be integrated with the real time
events, for better monitoring system (Alshamrani & Bahattab, 2015). Hence,
monitoring system is a crucial part that focuses not only on turning data into real
pictorial graphics, but also emphasizes the safety vehicles, distribution of road
conditions and real time tasks.

The context for the project is to study, analyze and compare the current
logistics route plans and create a new route planning so that its efficiency of
companies can be improved (Abraham et al, 2012). A new route planning is
proposed after the existing problems existing and faced by the distribution firms.
The purpose of the ‘monitoring system in logistics planning and
optimization’ explores the real time position of the logistics vehicles is detected
and analyzed, like speed and mileage (Arz et al, 2013). The modern logistics
requirements cannot be adapted by the traditional planning, like when a task is
performed by the logistics vehicle and a new task or an accident happens on the
road, the problem or issue, would be how to develop and propose a better alternate
route, still justifying the cost (Zhang et al, 2017). It needs the analysis of the
current road conditions on real time basis and plan should be developed towards a
better cost-effective path.
So, after the literature review and analysis, the final deliverable will be a
better and efficient monitoring system that is built the Application Interface
developed by Google Maps. This new system should be able to receive all the real
time information for the vehicle, such as fuel consumption, speed, loading capacity
and any relevant information to Google Maps, along with the feedback. A new path
will be created by refreshing the information regarding the vehicle information,
and relative condition of the road to the customized destination from the

customized start, for every 30 seconds. As a result, the monitoring system reflects
the direction towards distribution vehicle’s driving direction, for stakeholders to
check, on the Google Map (Antsfeld & Walsh, 2012).
LITERATURE REVIEW METHODOLOGY
Monitor system in logistics planning and optimization involves basically a
study of the route algorithms applied in the same companies and further a better
route algorithm is to be proposed after improving, through developing a new series
of applications. It should help and support courier corporations to improve the
driving path design, after analyzing the routes, intuitively, for artificially made
express cars.
Literature review is performed by searching and exploring the data about the
monitoring system. A crucial part concerned and focused in this context is the
algorithms that emphasize the distribution of road conditions, real-time tasks and
safety of vehicle, so that data analysis helps to make decisions towards benefiting
the society, by benefiting the companies and customers. To do so, initially, the way
the past algorithm or route planning schedules and methods are studied, followed
by the ways the methods to become better efficient methods, while addressing the
real time events (Bader et al, 2011). Further better methods proposals are explored,
to lower the shipping cost so that the short notice of customers, vehicle issues and
route availability demands can be addressed.

The existing literature has given the clue about the three difficulties that the
distribution corporations do face, usually, in the logistics in the cities. The first
difficulty is the relationship between travel time and time of the day, which can be
solved by exploiting a lot of data that is available today. The second problem
addressed is dynamics in cities. The third problem is the limitations of the
infrastructure, like few parking lots, narrow streets and one way.
Existing literature shows the current route planning of the current logistics
and also helps to investigate new ways and methods of planning route so that the
efficiency of these companies can be improved. After improvement of the existing
route planning, a monitor system is proposed to monitor the information of the
traffic, with reference to the speed routes, mileage, vehicles of the company
vehicles.
LITERATURE REVIEW
Logistics and Requirement
A new logistics industry generation development resulted in distribution
vehicles to increase in the same industry, gradually, however, gradually, the same
also has brought increased pollution, automobile exhaust and index of air quality is
gradually increased. Modern industry of logistics stands as a significant China’s
economic development component, so that the common economy and environment

sustainable development can be achieved, by necessitating reducing the
consumption of energy, in order to increase the green area (Bast et al, 2007). The
energy consumption is basically and mainly in the process of distribution, in the
logistics industry, towards achieving low energy consumption, the distribution
route problem is resolved and improved, using effective and reasonable algorithm,
to realize the optimization of distribution path to be a significant sustainable
development foundation and stands as the ultimate goal.
And another dimension for the logistics evolution challenges are various
methods used to predict the system of freight transportation, while representing
and analyzing. The challenge is found in a more detailed multimodal transportation
system network representation and the more refined demand development,
assignment models and mode choice (Bast & Storandt, 2014). This goal can be
achieved by focusing on these methodologies key component, the representation
and shortest paths computation. Hence, the route algorithms can be made user
optimal with the best route algorithm for shortest path routine. The best and
efficient algorithm should be explored appropriately, for appropriate applications,
in the logistics industry.
The basis for finding the shortest path for travelling, in the logistic industry
is the shortest path problem. An important issue to consider is the shortest paths
computation on networks, in this distribution that represent movements of freight

through multimodal systems (Batz et al, 2013). The paths modeling should take
only the modes to take into account, for making up the chain of transportation, but
also the way the networks of corresponding career and the operation of specific
logic distribution systems (Bast et al, 2007). A shortest path algorithm with
monitoring system has to be proposed and developed after studying and analyzing
the existing shortest path route algorithms.
Freight Networks Notation
The usual and regular problems considered are movement of, product flows
that are potentially different, in between the given points of origin and destination,
over networks of multimodal transportation. The transportation supply
representation takes the multimodal network form (Barrett et al, 2008). In this
context, mode is transportation means with certain characteristics like, vehicle
capacity, type and measures of cost.
Concept of Shortest Paths with Logistics Constraints
A shortest path is needed to visit a certain intermediate nodes set, in a
particular sequence, like particular vehicle’s itinerary. A conventional algorithm of
shortest path is applied to find shortest path, from the origin to each of the
intermediate node, followed by intermediate paths till the point of destination (Bast
et al, 2009). The problem needs to consider the path to use one successive node

sets that are not contiguous necessarily and permit the modes set’s any usage,
between such intermediate nodes successive set.
It should be noted that the intermediate node sets, in most of the cases as do
not form disconnect of the network. However, it implies that the problem cannot be
decomposed along sets of intermediate node. So, sub-paths have to be explored, till
satisfying paths that satisfy all the found constraints. However, it is determined
may be only in certain instances at the destination, in case a mode allowed in the
first set of constraint provides a complete path, while constraints are not satisfied
(Crainic et al, 2007).
Algorithms for Routing Planning
There are certain optimal algorithms existing for routing planning, such as IP
formulation. However, it is infeasible, computationally for obtaining the routing
planning solutions for the logistics applications. It is also indicated that generating
optimal solution for larger size routing planning is almost impossible, within
reasonable and small amount of time. Such problems can be solved, however, with
heuristics, replacing the optimal algorithms (Bast et al, 2013). Near-optimal
solutions can be obtained with several heuristic algorithms. Some of the important
algorithms are genetic algorithms, greedy, 3-opt, 2-opt, neural network, simulated
annealing though they have varied efficiencies from size to size and case to case.

Such algorithms can further be improved through non-crossing method (Hao &
Suling2009).
Routing Planning Algorithms
There are several heuristic algorithms exist for the logistic applications, for
routing planning.
Construction Algorithms
The key point and concept of the construction algorithm is to construct the
shortest path by including the points in the tour, until the development of the
complete tour, by including the points one by one (Batz and Sanders, 2012).
Improvement Algorithms
However, two or more points can be transposed in the initial tour, if
possible, in order to give an initial solution improvement, in improvement
algorithms. When improvement algorithm is considered, there are two stages
possible. There can be two alternate considerations to choose. The first one is to
choose one exchange, after considering all the possible exchanges, to obtain
greatest savings and let the process to continue till best possible reduction, further
(Bast et al, 2014). The second one is to make the exchange, as soon as a saving is
made available and examine other exchanges possible and let the process to
continue till the solution cannot be improved any further. The examples for the first