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The aim of this paper is to compare the performance of a local solutiontechnique -- namely Sequential Linear Programming (SLP) employing randomstarting points -- with state-of-the-art global solvers such as Baron and moresophisticated local solvers such as Sequential Quadratic Programming andInterior Point for the pooling problem. These problems can have many localoptima, and we present a small example that illustrates how this can occur.  We demonstrate that SLP -- usually deemed obsolete since the arrival of fastreliable QP solvers, Interior Point Methods and sophisticated global solvers --is still the method of choice for an important class of pooling problem whenthe criterion is the quality of the solution found within a given acceptabletime budget.  In addition we introduce a new formulation, the qq-formulation, for the caseof fixed demands, that exclusively uses proportional variables. We compare theperformance of SLP and the global solver Baron on the qq-formulation and othercommon formulations. While Baron with the qq-formulation generates weakerbounds than with the other formulations tested, for both SLP and Baron theqq-formulation finds the best solutions within a given time budget. Theqq-formulation can be strengthened by pq-like cuts in which case the samebounds as for the pq-formulation are obtained. However the associated timepenalty due to the additional constraints results in poorer solution qualitywithin the time budget.

On the Effectiveness of Sequential Linear Programming for the Pooling Problem