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• A human-jigger parasite system with control policies is established. • A time-optimal control problem with limited resources is proposed. • A numerical method combining the control parametrization scheme with the interior point algorithm is constructed. • A trade-off between the optimal eradication time and the effective funding is provided. Tungiasis, as an epidermal parasitic skin disease, leads to long-term injury and life threats to humans in resource-limited countries. In this paper, we aim to minimize the epidemic duration of tungiasis disease with limited resources. A human-jigger parasite system with four control policies for humans and jiggers is established. We propose a time-optimal control problem, in which the eradication time and limited resources are involved. By applying the Pontryagin's minimum principle, we prove that, only bang-bang controls are admitted for all the control policies. Furthermore, a numerical scheme combining the control parametrization scheme with the interior point algorithm is constructed. Finally, numerical simulations are carried out using actual data of humans and jiggers in Brazil. From all the results, we conclude that, there is a trade-off between the optimal eradication time and the effective funding; once the effective funding is properly used, the disease can be controlled effectively; strengthening personal protections, improving treatments for humans and making adulticiding efforts contribute to keeping humans away from the disease. [ABSTRACT FROM AUTHOR]

Abstract: Goal Programming (GP) is an important analytical approach devised to solve many realworld problems. The first GP model is known as Weighted Goal Programming (WGP). However, Multi-Choice Aspirations Level (MCAL) problems cannot be solved by current GP techniques. In this paper, we propose a Multi-Choice Mixed Integer Goal Programming model (MCMI-GP) for the aggregate production planning of a Brazilian sugar and ethanol milling company. The MC-MIGP model was based on traditional selection and process methods for the design of lots, representing the production system of sugar, alcohol, molasses and derivatives. The research covers decisions on the agricultural and cutting stages, sugarcane loading and transportation by suppliers and, especially, energy cogeneration decisions; that is, the choice of production process, including storage stages and distribution. The MCMIGP allows decision-makers to set multiple aspiration levels for their problems in which “the more/higher, the better” and “the less/lower, the better” in the aspiration levels are addressed. An application of the proposed model for real problems in a Brazilian sugar and ethanol mill was conducted; producing interesting results that are herein reported and commented upon. Also, it was made a comparison between MCMI GP and WGP models using these real cases. [Copyright &y& Elsevier]