Models in this form are actually called bilinear optimization problems. The typical approach to linearizing bilinear terms is through something called the McCormick envelope. Consider variables x and y, where you want x*y in the objective of your maximization problem. If we assume x and y are bounded by xL <= x <= xU and … Read more
A good answer is dependent on what you mean by “convex” and “more general” If you are trying to solve large or challenging linear or convex-quadratic optimization problems (especially with a discrete component to them), then it’s hard to beat the main commercial solvers, gurobi, cplex and Dash unless money is a big issue for … Read more
I personally found GLPK better (i.e. faster) than LP_SOLVE. It supports various file formats, and a further advantage is its library interface, which allows smooth integration with your application.