Percorrer por autor "Barros, Telmo"
A mostrar 1 - 3 de 3
Resultados por página
Opções de ordenação
- Economic and food safety: optimized inspection routes generationPublication . Barros, Telmo; Oliveira, Alexandra; Cardoso, Henrique Lopes; Reis, Luís Paulo; Caldeira, Cristina; Machado, João PedroData-driven decision support systems rely on increasing amounts of information that needs to be converted into actionable knowledge in business intelligence processes. The latter have been applied to diverse business areas, including governmental organizations, where they can be used effectively. The Portuguese Food and Economic Safety Authority (ASAE) is one example of such organizations. Over its years of operation, a rich dataset has been collected which can be used to improve their activity regarding prevention in the areas of food safety and economic enforcement. ASAE needs to inspect Economic Operators all over the country, and the efficient and effective generation of optimized and flexible inspection routes is a major concern. The focus of this paper is, thus, the generation of optimized inspection routes, which can then be flexibly adapted towards their operational accomplishment. Each Economic Operator is assigned an inspection utility – an indication of the risk it poses to public health and food safety, to business practices and intellectual property as well as to security and environment. Optimal inspection routes are then generated typically by seeking to maximize the utility gained from inspecting the chosen Economic Operators. The need of incorporating constraints such as Economic Operators’ opening hours and multiple departure/arrival spots has led to model the problem as a Multi-Depot Periodic Vehicle Routing Problem with Time Windows. Exact and meta-heuristic methods were implemented to solve the problem and the Genetic Algorithm showed a high performance with realistic solutions to be used by ASAE inspectors. The hybrid approach that combined the Genetic Algorithm with the Hill Climbing also showed to be a good manner of enhancing the solution quality.
- Generation and optimization of inspection routes for economic and food safetyPublication . Barros, Telmo; Oliveira, Alexandra; Cardoso, Henrique Lopes; Reis, Luís Paulo; Caldeira, Cristina; Machado, João Pedro; Oliveira, AlexandraArtificial intelligence techniques have been applied to diverse business and governmental areas, in order to take advantage of the huge amount of information that is generated within specific organizations or institutions. Business intelligence can be seen as the process of converting such information into actionable knowledge, which is the basis for data-driven decision making. With this in mind, this work is framed in a project that seeks to improve the activity of the Portuguese Food and Economic Safety Authority, regarding prevention in the areas of food safety and economic enforcement. More specifically, this paper focuses on the generation and optimization of flexible inspection routes. An optimal inspection route seeks to maximize the number of targeted Economic Operators, or the utility gained from the set of Economic Operators that are actually inspected. For that, each Economic Operator is assigned an inspection utility value. The problem was then modelled as a Multi-Depot Periodic Vehicle Routing Problem with Time Windows, and solved using both exact and meta-heuristic methods. The comparison of the meta-heuristic algorithms showed a versatile Hill Climbing implementation in different test cases that explored the effect of the Economic Operators dispersion and density.
- Interactive inspection routes application for economic and food safetyPublication . Barros, Telmo; Santos, Tiago; Oliveira, Alexandra; Cardoso, Henrique Lopes; Reis, Luís Paulo; Oliveira, AlexandraThis paper describes an application aimed at improving the current state of enforcement in the areas of food safety and economic activities in Portugal. More specifically, the application focuses on a flexible and interactive approach to generate inspection routes, to be followed by surveillance brigades with the aim of verifying Economic Operators’ compliance to national and European legislation on economic and food safety. The problem is modeled as a Multi-Depot Periodic Vehicle Routing Problem with Time Windows, and the algorithmic approaches employed seek to maximize either the number of inspected Economic Operators or a utility function that takes into account the utility gained from inspecting each Economic Operator. The generated solutions are shown in an intuitive platform, where human operators can visualize the solutions details (including georeferenced locations in a map) and fully customize them on time by manually removing or adding Economic Operators to be targeted.