Nowadays, optimization became crucial in most business
sectors, but theoretical results do not find practical implementations in
technology so fast to be used by real life business. This work is one of the
rare examples of multidisciplinary work which combines the new theoretical
results and implements the practical application of
optimization methods. This paper presents a computational implementation
of some vehicle routing problems (VRP), mainly on pickup and delivery problems,
introduces recent theoretical results put forward by a survey on types of VRPs
and explains the features of the software implemented based on the research.
The vehicle
routing problem (VRP) is a combinatorial optimization and nonlinear programming
problem seeking to service a number of customers with a fleet of vehicles.
Proposed by Dantzig and Ramser in 1959, VRP is an important problem in the
fields of transportation, distribution and logistics. [cf. wikipedia.org]
The Vehicle Routing Problem (VRP) is a well
known problem in operational research where customers of known demands are
supplied by one or several depots. The objective is to find a set of delivery and
pick-up routes satisfying some requirements or constraints and giving minimal
total cost. It is important for companies that plan routes and schedule fleet on
a regular basis to ensure that the routes are up-to-date, economical and
efficient.
Goods, passengers, mail posts are some examples
of the transported objects. The aim of the solution of a VRP is usually to find
the minimum cost or distance by serving maximum number of customer requests (or
orders) subject to some constraints. Those constraints are important to implement effectively
to VRP and it is useful to list all restrictions that can potentially apply.
Vehicles are the key
element of vehicle routing problem. Each vehicle has a limit (capacity -
usually weight and/or volume) on the goods or passengers carried. Each vehicle
has a total working time from departure to arrival back at the depot and each
vehicle has a time period within which it must leave the depot. Moreover, each
vehicle has a number of time periods that must be taken into consideration for
vehicle routing problem.
Another key element of
the vehicle routing problem is orders. Order can be defined as your goods, passengers
have a certain quantity which has to be delivered (and/or collected), and to be
picked up. Orders also can be services to provide to customer at some
locations, such as the customer location.
After taking those
constraints into consideration, it is an important aim to meet the above
requirements. There are a number of objectives that could be adopted. To solve
vehicle routing problem effectively, it is important to minimize the number of vehicles
used. It might minimize the total distance and time.
In this way, users can
reach their goal that they can make a profit while saving their time and
maximizing customer satisfaction.
Vehicle route planning and scheduling is a hard and time consuming task. Most
companies even do not plan routes or schedules. This makes their operations
costly and inefficient. We have produced logvrp, a web based SaaS application
that does vehicle route planning and scheduling. It helps users to manage their
operational, transportation activities, field workforce optimization. Our goal
is to give the best solution to users’ vehicle routing problem and provide
effective route planning and scheduling solutions all around the world. You can
check it at: http://logvrp.com
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