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Logistic resources planning system to assist users geographically dispersed

Grant number: 15/15969-2
Support type:Research Grants - Innovative Research in Small Business - PIPE
Duration: March 01, 2016 - November 30, 2016
Field of knowledge:Engineering - Production Engineering - Operational Research
Principal Investigator:Bruno Jensen Virginio da Silva
Grantee:Bruno Jensen Virginio da Silva
Company:Neoinfinito Softwares - Eireli
City: São Carlos
Co-Principal Investigators:Denise Sato Yamashita
Associated grant(s):16/17707-8 - Emergency services planning system to users geographically dispersed, AP.PIPE
Associated scholarship(s):16/02360-2 - Logistic resources planning system to assist users geographically dispersed, BP.PIPE
16/02376-6 - Logistic resources planning system to assist users geographically dispersed, BP.PIPE

Abstract

Some services have as characteristic serve users who are geographically dispersed, make calls and awaiting the displacement of resources as winch vehicles or ambulances to provide the service. Logistics systems with these characteristics are called in the literature as spatially distributed queues and are represented as hypercube models. The planning of these systems is a difficult task because the arrivals rates, types, travel, services and return to the base times and the location of the users are random and change with time.The highway administration companies must to provide multiples services called SAU such as vehicle assistance, firefighting, pre-hospital care and capture of animals in the highways under its responsibility as specified on contract. These services have performance levels defined in the concession contracts and are routinely audited by the government, therefore, they are important to the highway administration companies.The aim of this research project is to develop quantitative methods to assist the highway administration companies in planning their SAU operations economically and respecting the contractual performance requirements. For that will be researched and adapted computational methods, built prototypes based on queuing theory and combinatorial optimization algorithms and validated with realistic scenarios, representing highways administration companies.The main research challenges are to develop and validate extensions of the hypercube models capable of representing the SAU and integrate them with combinatorial optimization algorithms that will suggest decisions like positioning settings , coverage areas and others, generating performance levels better than the performance the decisions of the highway administration companies. Decisions are suggested based on the data recorded in the information systems of companies, so the methods have the ability to identify and adapt to changing events over time. To do that, the algorithms must be developed, tested and parameterized to find good solutions in small computational times. Due to the random nature of multiple aspects of these systems, the validation of the quality of the suggested solutions need to use statistical methods and discrete event simulation experiments.The planning of this type of service is important from an economic point of view, because the Brazilian private administered highway system involves about 14,000 km, 2000 vehicles to provide services to the users and more than 2 million calls per year, so, it is a large and complex system. It is also important the impact on society, particularly in the services involving medical emergency and rescue which the response time can affect the chances of survival of users victims of accidents on the highways. This technology can also be applied to various other logistics systems and similar service, including in urban areas, with equal relevance to society.Planning systems with spatially distributed queues have great importance for being difficult problems to resolve, involve significant investments of companies and government and impacting various services and aspects of people's lives and consumers. The private administrated highway system in Brazil and its SAU also has great economic importance because they represent about 14,000 kilometers of roads, over 2000 vehicles to serve the users, 1.5 million vehicle traffic and more than 2 million calls per year and, therefore, is a large and complex system. Another important impact is the social factor, especially in services involving medical emergency and rescue which the response time can affect the chances of survival of users victims of accidents on the highways. This technology can also be applied in many other similar logistics systems and services, including in urban areas, with equal relevance to society. (AU)