Post-Model Analysis (PMA) is a framework that unifies an optimization model with a rule-based system and enables the multi-objective decision modeling that considers both numeric and symbolic objectives and decision variables. In this research, we have developed a system UNIK-PMA that implements the PMA procedure on the knowledge-assisted optimization modeler UNIK-OPT and a backward chaining rule-based system UNIK-BWD. This paper particularly elaborates the process of generating constraints of the linear programming model from the rule-based goals, which is a crucial step of PMA. UNIK-PMA is illustrated with an example of aggregate production planning.