A processor implemented method comprising: receiving, via one or more hardware processors, a plurality of rules comprising one or more variables of one or more operations of air handling units (AHUs), wherein the one or more variables of the one or more operations include occupancy count, ambient temperature of an establishment, a return air temperature, a flow rate of an AHU fan of the establishment, a discomfort level of the occupants and consumed energy; verifying using a test case generation framework that converts the received plurality of rules in a form of an Expressive Decision Table to identify one or more rule sets having conflicting conditions, wherein the conflicting conditions refer to a condition when two or more rules activate a device in a contradictory manner at a same time; determining, using an integrated framework during different runs, frequency of the one or more rule sets having conflicting conditions, wherein the test case generation framework is integrated with a building energy model using a co-simulation paradigm, wherein the test case generation framework generates variables occupancy count, ambient temperature and estimates a value of flow rate according to the rules using a return air temperature given by the building energy model; generating, based on the frequency of the one or more rule sets having conflicting conditions, a ranked list of the one or more rule sets having conflicting conditions; identifying, one or more rules based on a selection of at least one rule set from the ranked list of the one or more rule sets and a performance criteria; and dynamically optimizing, one or more parameters of AHUs specific to the performance criteria including at least one of the consumed energy, the discomfort level based on the identified one or more rules, wherein from the identified one or more rule sets having only a pair of rules, a rule flipping mechanism is performed to change a sequence of rules in the EDT, wherein the rule flipping mechanism is modified based on mapping the rules with the performance criteria, wherein the rule flipping mechanism achieves a balance between the consumed energy and comfort by selecting conflicting rules with highest frequency. receiving, via one or more hardware processors, a plurality of rules comprising one or more variables of one or more operations of air handling units (AHUs), wherein the one or more variables of the one or more operations include occupancy count, ambient temperature of an establishment, a return air temperature, a flow rate of an AHU fan of the establishment, a discomfort level of the occupants and consumed energy; verifying using a test case generation framework that converts the received plurality of rules in a form of an Expressive Decision Table to identify one or more rule sets having conflicting conditions, wherein the conflicting conditions refer to a condition when two or more rules activate a device in a contradictory manner at a same time; determining, using an integrated framework during different runs, frequency of the one or more rule sets having conflicting conditions, wherein the test case generation framework is integrated with a building energy model using a co-simulation paradigm, wherein the test case generation framework generates variables occupancy count, ambient temperature and estimates a value of flow rate according to the rules using a return air temperature given by the building energy model; generating, based on the frequency of the one or more rule sets having conflicting conditions, a ranked list of the one or more rule sets having conflicting conditions; identifying, one or more rules based on a selection of at least one rule set from the ranked list of the one or more rule sets and a performance criteria; and dynamically optimizing, one or more parameters of AHUs specific to the performance criteria including at least one of the consumed energy, the discomfort level based on the identified one or more rules, wherein from the identified one or more rule sets having only a pair of rules, a rule flipping mechanism is performed to change a sequence of rules in the EDT, wherein the rule flipping mechanism is modified based on mapping the rules with the performance criteria, wherein the rule flipping mechanism achieves a balance between the consumed energy and comfort by selecting conflicting rules with highest frequency.