Global Optimal Algorithm for Linear Programming Problems Subjected to Nonlinear Constraints
Yang Ju · Yunchou yu guanli · 2007
A new global optimal algorithm is presented to solve linear programming problems with nonlinear constraints.In this algorithm,a subproblem is set up to search for a new feasible point at which the value of the objective function is lower than the current local minimum.The subproblem is solved by simulated annealing algorithm.Through solving a sequence of subproblems,the current optimal feasible solution can be incessantly renewed and the global optimal solution can be got at last.Finally,this algorithm is applied to some test problems and it has the better results than using the penalty function algorithm.