2020/04/09 by Michel De Lara, Michel de Lara, de Lara, Michel +4
Biochemistry, Genetics and Molecular Biology · Computer Science · Engineering · Mathematics · #Advanced Control Systems Optimization #Bayesian Modeling and Causal Inference #Computer science #Conic section #FOS: Mathematics #Gene Regulatory Network Analysis #Geometry #Mathematics #Optimization and Control (math.OC) #math.OC
paper · pdf · doi:10.48550/arxiv.2004.04473
openalex publication_date 2020/04/09 · openalex created_date 2020/04/17 · arxiv created 2020/07/21 · arxiv updated 2020/07/22 · openalex updated_date 2026/08/08
In natural resource management, decision-makers often aim at maintaining\nthestate of the system within a desirable set for all times.For instance,\nfisheries management procedures include keeping thespawning stock biomass over\na critical threshold.Another example is given by the peak control of an\nepidemic outbreakthat encompasses maintaining thenumber of infected individuals\nbelow medical treatment capacities.In mathematical terms, one controls a\ndynamical system.Then, keeping the state of the system within a desirable set\nfor all times is possible when the initial state belongs to the so-called\nviabilitykernel. We introduce the notion of conic quasimonotonicity\nreducibility.With this property, we provide a comparison theorem by inclusion\nbetween two viabilitykernels, corresponding to two control systems in the\ninfinite horizon case. Wealso derive conditions for equality. We illustrate the\nmethod with a model for thebiocontrol of a vector-transmitted epidemic.\n