This self-study course was designed to help you study mathematical programming for agricultural and environmental economics on your own, at your own pace and according to your learning needs.
By clicking on a sequence, you will have access to its different units, which are in turn divided into lessons and activities (MCQs and model construction). You can watch the recorded lecture and download the relevant slideshow for each unit. You may choose to do the exercises at the end of every lesson, or to work on all the lessons within one unit before you start on the exercises, which you do not all have to do. Each unit offers a “Self-assessment” section, which allows you to put these newly developed skills into practice.
Model construction activities may use models previously described in other units. If you have not done the activity in question, you may find the relevant model in the “Model library”.
The first suggested 20 hour basic course is found under 
. The full course, 
, represents around 35 hours of study.
All the best !
| Sequence | Description |
| 1 – Introduction to mathematical programming using GAMS | The first sequence includes the basics of mathematical programming and an introduction to GAMS. Based on a simple model of a cereal farm that grows wheat and maize, a mathematical programming model is developed, first of all in algebraic form represented graphically, and then using GAMS. This first model introduces the basic elements of GAMS for model construction. The sequence ends with a short presentation of dual values and their use. |
| Components of GAMS language : model structure, .lst, display, .up, .lo, .m, and GDX (import and export of data in Excel) files | |
| 2 – Farm modelling | Throughout this second sequence the basic model is extended with the introduction of production techniques, of constraints per period, and of the possibility of access for production factors. The introduction of multi-periodic decisions into annual models such as rotations, livestock or accounts must then be considered. These enriched models eventually make it possible to carry out simulations of environmental public policies. |
| Components of GAMS language : two-dimensional variables, three-dimensional tables, LOOP, subsets, binary variables | |
| 3 – Risks and time factors in models | The third sequence is divided into two parts. The first one deals with risk and begins with a reminder of risk in agriculture, and various methods are highlighted : Safety-First, variance-standard deviation approach, Chance Constrained Model, Target-MOTAD and utility function. In the second part, which deals with time in the models, dynamic models are presented, two of which are in more detail : recursive models and multi-periodic models. |
| Components of GAMS language : NLP, exponential function, square root, cardinal, $ condition, exponent |