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The coordination of physical flows, information flows, and financial flows is nowadays essential to guarantee economic profitability and ensure the company's sustainability. Time differences between physical operating flows and cash flows create financing needs within the company. These needs must be optimised at the same time as logistical decisions and can have a considerable impact on the company's overall performance. Recently, with the Coronavirus disease 2019 crisis and the period of containment, many companies are suffering from a lack of liquidity due to the closure of certain companies. While considering this health crisis, the authors design two mathematical models: one before containment and the second after containment. In the latter, they propose a solution to the payment problem in order to improve working capital performance. They use the genetic algorithm to solve the two mathematical models, and they run simulations first on a real dataset from a dairy cooperative and subsequently on a second dataset available online.

Modeling Financial Supply Chain Planning Under COVID-19 Conditions for Working Capital Optimization Through Genetic Algorithm: A Real Case Study