Modelling and solving environments for mathematical programming (MP): a status review and new directions

Languages and computing environments that support Mathematical Programming (NIP) modelling continue to develop and evolve. In this paper: (i) We address declarative and procedural features of modelling languages. (ii) We assess developments which couple the modelling and the solving processes, typically column generation, the branch-and-price approach to Integer Programming (IP), and the sampling of scenarios within Stochastic Programming (SP). (iii) We consider how data modelling and symbolic modelling naturally come together and are used within the information value chain. (iv) Finally, we investigate the features of new tools, which support prototyping of optimisation based Decision Support (DS) applications.