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