When faced with a problem related to decision support, the first (and most important) step is to analyze the problem in order to build a mathematical model. This model responds to a thinking process called « scientific method » which consists of five steps:
- Mathematical aspects: the analysis of the specifications allows to highlight the constraints and the objectives of the models. Constraints and objectives must be able to be written using algebra and logic.
- Modeling: following the mathematical understanding of the problem, the modeling step consists in finding the best tool to represent the model. Among these tools, we can cite graph theory, game theory, linear programming, constraint programming etc.
- Analysis and resolution: following the modeling, you must be able to analyze the complexity in time and space of the model after having modeled it in an algorithmic point of view.
- Implementation and results: we must find the best way to implement the algorithm, whether in programming method or in language to create the most relevant and efficient software possible.
- Deployment of solutions: the last step is to validate the created model by solving other problems of the same form as the original one.