A MIXED-INTEGER OPTIMIZATION STRATEGY FOR A LARGE-SCALE CHEMICAL-PLANT IN OPERATION

Over the last 10 years much effort has been devoted to the study of op timization strategies for models involving both continuous and integer variables (Mixed-Integer Nonlinear Programming (MINLP) formulations). Several algorithms have been proposed and a large number of research applications have been presented. However, only a few applications hav e been reported for real large scale plants. This paper presents the s tructural and operational optimization of a real ethylene plant in ope ration. A procedure is used involving the Outer-Approximation (OA) met hod for the MINLP problem and an existing ad-hoc simulator. The optimi zation algorithm interfaces the simulation code at the nonlinear progr amming step. The model handles four continuous independent variables, 33 integer variables, more than 200 dependent variables and 48 process constraints. As compared with the best continuous solution, the resul ts show that an increase of 296,337 US$/yr in gross profit can be obta ined by simultaneous parameter and structural optimization using a MIN LP model. This study also shows that the OA method works very well on real problems reaching convergence in few iterations. This characteris tic makes the method a practical tool for large applications, and conf irms its potential to be introduced as a standard option in commercial process simulators.