Generating scalable optimization and multi-agent research models from high-level analytical descriptions: Long-term and medium-term forecasts for the economic and energy sector development

Economic forecasts for decision-making and research purposes are usually based on fairly complex models. Once created, models often require updates to meet new requirements and/or implement new methodology. This paper considers modelling tools, which allow non-programming specialists to build efficient executable models from analytical description written in high-level domain-specific language and provide extensibility when new modelling methodology needs to be added. Current implementation allows users to create linear and multi-linear optimization models (to find and analyze the best possible scenarios of economic development), and multi-agent models (to use behavioral rules for more precise economic analysis, especially for the crisis periods).