Optimal dynamic control of predator–prey models

Abstract

This paper combines work to use a decision support tool for sustainable economic development, while acknowledging interdependent dynamics of population density, and interferences from outside. We get new insights derived from experimental approaches: analytical models (optimal dynamic control of predator-prey models) provide optimal dynamic strategies and interventions, depending on different objective functions. Our economic experiments are able to test the applicability of these strategies, and in how far decision-makers can learn to improve decision-making by repeated applications. We aim to analyse a sustainable environment with diametrical goals to harvest as much as possible while allowing optimal population growth. We find interesting insights from those who manage the dynamic system. With the methodology of experimental economics, the experiment at hand is developed to analyse the capability of individual persons to handle a complex system, and to find an economic, stable equilibrium in a neutral setting. We have developed a most interesting simulation model, where it will turn out that prices play a less important role than availability of the goods. This aspect could become a new important aspect in economics in general and in sustainable environments especially.

A Reconceptualization of Social Bond Theory to Predict Change Sequences in Offending

“…Finally, as the predator populations decrease, prey populations eventually increase because of the reduced predation (B t4 → A t5 ). In short, the sequence involves lag effects that alternate from positive to negative: The model has many applications in ecology (Abrams, 2000;Hold & Bonsall, 2017) but also to areas outside of ecology, such as economics (Becker & Leopold-Wildburger, 2020;Wang & Wang, 2016). Like any model, it simplifies reality through assumptions.…”

“…The model has many applications in ecology (Abrams, 2000; Hold & Bonsall, 2017) but also to areas outside of ecology, such as economics (Becker & Leopold-Wildburger, 2020; Wang & Wang, 2016). Like any model, it simplifies reality through assumptions.…”

Nonlinear optimal and flatness-based control for the multivariable Lotka-Volterra dynamics

“…The multivariable Lotka-Volterra model has been primarily conceived to describe the interaction of competing populations (Ye et al, 2022), (Massaroli et al, 2020), (Zhang et al, 2015), (Tiao et al, 2021). It has found ample use in biology, ecology, agricultural production management or even in economics (Chakraborty et al, 2011), (Becker and Leopoldo-Wildburger, 2020), (Aranth and Vomsi, 2021). The model is also known as the prey-predator system, and its state variables represent the population of prey and predator species (Babaci and Shafiee, 2019), (Li et al, 2018), (Qian et al, 2010).…”

Stability Analysis of Dynamical Model Interactions Tea Plants, Pests, and Diseases With Fungicides and Insecticides Controls

“…In Dipo Aldila's research, the controls are given for covid model. In this paper, we combined [6][7][8] migrating and interaction beteween pest and disease that applied for tea plantation by adding the optimal control. So, the differences between this model and the research before are this research modified the dynamic model with remove migrating population, interaction between pest and disease, and add the control [9][10][11].…”