Dr Alysson M. Costa

and Simon Bowly

Optimising crop rotation schedules

In the first part of this hands-on session, we will present a crop rotation problem in the context of sustainable vegetable production. We will develop a compact mixed-integer programming model, which will be implemented and solved with free online optimisation tools (JuliaBox/JuMP/Cbc).  In the second part, the crop rotation model will be extended to include plot area planning in order to satisfy required demands.  The new formulation has a large number of variables and we will present and implement a delayed column generation method for the efficient obtention of solutions.

Dr Alysson M. Costa

Senior Lecturer, School of Mathematics and Statistics, The University of Melbourne

Alysson M. Costa is a Senior Lecturer in Operations Research at the School of Mathematics and Statistics – University of Melbourne. Alysson is interested in theory and applications of Optimisation. Throughout his career, he has worked extensively with mixed integer programming (modelling and solution methods) applied to problems in different areas such as environmental water management, disaster relief operations, educational timetabling, crop rotation, assembly line balancing and city logistics, among others.

He received his PhD in 2006 from HEC Montreal / University of Montreal – Canada. His thesis, titled “Models and algorithms for two network design problems”, received the Cecil Graham doctoral dissertation award from the Canadian Applied and Industrial Mathematics Society. Before that, he received MSc. and B.Eng. Degrees in Electrical Engineering from the State University of Campinas – Brazil.

Simon Bowly

School of Mathematics and Statistics, The University of Melbourne

Simon Bowly is currently completing his PhD in the School of Mathematics and Statistics at the University of Melbourne, focusing on generating test cases that effectively stress-test optimisation algorithms.His work aims to address the lack of instance diversity in existing test sets in order to aid researchers in assessing algorithm strengths and weaknesses. He has a strong interest in algorithm development, empirical performance analysis, and automated algorithm configuration using machine learning methods. Simon has extensive experience applying optimisation and data analysis techniques to real-world problems. He is currently the lead developer for SCADA Miner, building automated tools to analyse wind farm operational data and identify performance and maintenance issues. Previously, he has worked as a consultant with Biarri Optimisation, focusing on road and rail logistics projects.