出版社：Institute for Operations Research and the Management Sciences
摘要：Excel's built-in Solver optimiser provides millions of spreadsheet users with easy access to optimisation, and is often used in teaching introductory optimisation courses. However, more sophisticated users often prefer to use modelling languages such as AMPL, GAMS, or PuLP, and so these are often taught in more advanced courses. Unfortunately, the command line and text file interfaces these systems employ present unnecessary barriers to their use. We have developed a new free Excel add-in, SolverStudio, that combines the power of modelling languages—including AMPL, GAMS, PuLP, GMPL, and Gurobi's Python environment—with the familiarity and ease of use of Excel. SolverStudio also brings cloud-based optimisation to Excel by providing easy access to the NEOS online solvers, and simulation capabilities via the Python-based SimPy software. We believe that SolverStudio will support and encourage the greater use in classrooms of Excel-based optimisation and simulation.
