Real-time fleet management decision support system with security constraints
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Real‑time fleet management decision support system with security constraints Javiera Barrera1 · Rodrigo A. Carrasco1 · Eduardo Moreno1 Received: 30 December 2019 / Accepted: 22 April 2020 © Sociedad de Estadística e Investigación Operativa 2020
Abstract Intelligent transportation, and in particular, fleet management, has been a forefront concern for a plethora of industries. This statement is especially true for the production of commodities, where transportation represents a central element for operational continuity. Additionally, in many industries, and in particular those with hazardous environments, fleet control must satisfy a wide range of security restrictions to ensure that risks are kept at bay and accidents are minimum. Furthermore, in these environments, any decision support tool must cope with noisy and incomplete data and give recommendations every few minutes. In this work, a fast and efficient decision support tool is presented to help fleet managers oversee and control ore trucks, in a mining setting. The main objective of this system is to help managers avoid interactions between ore trucks and personnel buses, one of the most critical security constraints in our case study, keeping a minimum security distance between the two at all times. Furthermore, additional algorithms are developed and implemented, so that this approach can work with real-life noisy GPS data. Through the use of historical data, the performance of this decision support system is studied, validating that it works under the real-life conditions presented by the company. The experimental results show that the proposed approach improved truck and road utilization significantly while allowing the fleet manager to control the security distance required by their procedures. Keywords Fleet management · Real-time control · Data analytics · GPS tracking · Decision support system · Conflict detection and resolution Mathematics Subject Classification 90B06 · 90B20 · 90B50 · 90B90 * Eduardo Moreno [email protected] Javiera Barrera [email protected] Rodrigo A. Carrasco [email protected] 1
Faculty of Engineering and Sciences, Universidad Adolfo Ibáñez, Santiago, Chile
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1 Introduction Within the process of ore production, the efficient transportation of materials from the different parts of the mine is of the uttermost importance. In many mining operations, transportation of ore, intermediate products, and personnel accounts for a relevant fraction of the overall costs (Rojas et al. 2015). Correct management not only helps in keeping production costs at bay, but also ensures the flow of the required materials onto the cascading activities in the production process; having the needed materials on time, in turn, improves overall equipment effectiveness and increases production rates. Given its importance, fleet management has been a relevant research topic for many decades (Dejax and Crainic 1987). Furthermore, the implementation of intelligent transportation systems has been at the
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