The programming committee for the 77th Annual SAM International Business Conference is pleased to announce the acceptance of the panel presentation Optimal Control Models Of A Biological Invader Using Gaussian Kernels, authored Sevilay Onal, Sabah Bushaj, Esra Toy, Gregory Houseman and Jennifer Smith from the University of Illinois Springfield, SUNY Plattsburg, NJIT, and Wichita State University.
Presentation Abstract: Sericea lespedeza was recognized as a biological invader in the Federal Noxious Weed Act in 2000. The response of the federal government of the U.S. is to sustain and expand efforts by preventing, eliminating, and controlling invasive species, as well as restoring ecosystems and other assets impacted by invasive species. Strategies to control infestation have been designed to reduce the harmful impacts on biodiversity and bioeconomy. Thus, the determination of optimal control methods is crucial. In this paper, we present an integrated simulation-optimization model that mimics the growth and control of the weed. The simulation model estimates the natural means of seed dispersal using Gaussian cell-to-cell transition probabilities as well as random or unexpected ways. The bio-economic optimization model prescribes treatment locations over a predetermined time period depending on the infestation level on a limited budget. Our case study data and parameter calibration are based on large-scale field data collected over eighteen pastures in Kansas and Oklahoma during the past five years. We simulate Sericea growth over a landscape for 25 years and optimize the search and treatment locations while minimizing its economic damage to forage production in Kansas under a restricted budget. The results of the simulation-optimization framework provide insight into the optimal treatment frequency, optimal search speed, and cost-benefit analysis of treatment under various invasion and seed dispersal scenarios.
Join us online to see this great paper and many more March 31 – April 2, 2022. For registration information visit www.samnational.org/conference.