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This paper presents a mobile app developed to optimize the drone flight in a precision agriculture scenario. The Android platform was chosen, once it have free tools for development and there are many different API that could be used to solve this problem. For map presentation, as well as geocoding manipulation, Google tools were used. For the optimization, an algorithm based on recursive auctions was used, which has the characteristic of finding feasible solutions even in complex scenarios. The app has been tested and achieved feasible results for large scenarios with over a thousand waypoints in just few minutes, even running on a mobile device. It highlights the mobile app, and the recursive auction algorithm, it is an important solution for drone flight optimization in rural areas, where thereis usually no possibility to run the application on traditional computers, as usually there is no access to the Internet.

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This work presents and evaluates the performance of a simulation model based on multiagent system technology in order to support logistic decisions in a harbor from oil supply chain. The main decisions are concerned to pier allocation, oil discharge, storage tanks management and refinery supply by a pipeline. The real elements as ships, piers, pipelines, and refineries are modeled as agents, and they negotiate by auctions to move oil in this system. The simulation results are compared with results obtained with an optimization mathematical model based on mixed integer linear programming (MILP). Both models are able to find optimal solutions or close to the optimal solution depending on the problem size. In problems with several elements, the multiagent model can find solutions in seconds, while the MILP model presents very high computational time to find the optimal solution. In some situations, the MILP model results in out of memory error. Test scenarios demonstrate the usefulness of the multiagent based simulator in supporting decision taken concerning the logistic in harbors.Keywords: oil industry supply chain; inventory management; multiagent system; MILP. ResumoO objetivo deste artigo é apresentar e avaliar o desempenho de um modelo de simulação baseado em sistemas multiagentes para auxiliar a tomada de decisão na alocação de petróleo em complexos portuários. Os diversos elementos do problema são modelados como agentes e negociam por meio de leilões a alocação dos inventários de óleo. Os resultados obtidos são comparados com resultados gerados por modelos de otimização matemática, estes baseados em programação linear inteira mista. Esses modelos são capazes de encontrar soluções ótimas ou próximas da ótima dependendo do tamanho da instância testada. Em problemas com muitos navios e tanques, o modelo baseado em sistema multiagente encontrou soluções em segundos, enquanto os modelos baseados em otimização matemática apresentaram problemas de tempo computacional e falta de memória, não encontrando a solução ótima. Os diversos exemplos aqui apresentados evidenciam a necessidade do modelo de simulação baseado em multiagentes no auxílio a tomada de decisões logísticas de portos Palavras-chave: cadeia de suprimento de petróleo; alocação de inventário; sistema multiagente; PLIM.Brito, Tacla & Arruda -A multiagent simulator for supporting logistic decisions of unloading petroleum ships in habors 730Pesquisa Operacional, v.30, n.3, p.729-750, Setembro a Dezembro de 2010