APPLICATION OF THE ANT COLONY ALGORITHM TO OPTIMIZE THE SYNTHESIS OF HEAT-INTEGRATED DISTILLATION SEQUENCES FOR 6-COMPONENTS (C4-C7)

This study develops a meta-heuristic technique in order to synthesize distillation systems with multiple components. The most appropriate structure for the process of chemical separation can most readily be accomplished by the correct rearrangement of distillation when the costs are taken into account. The process developed involves an encoding system using an integer number series which can manage the system's flow sheet structure. The general problem of synthesis using the representation procedure can be formulated as an implicit MILP (mixed-integer linear programming) problem. Two meta-heuristic approaches are discussed in this study: the ant colony algorithm (ACO) and the harmony search algorithm (HS). For both algorithms, the parameters seek the optimal value for application, and subsequent checking using ANOVA with a confidence level of 95%. The outcomes are then compared in order to make improvements to address the problem. Large scale 6-component (C4-C7) problems are examined in the study in order to demonstrate the techniques.