1. A method for network resource optimization in a service area of a communication network, the method comprising: computing, by a processor, a pre-requisite number of network resources based on a plurality of parameters associated with a plurality of objectives for network resource optimization, one or more constraints associated with the network resources, and influences parameters associated with the service area to meet one or more objectives of the plurality of objectives, wherein the network resources comprises a plurality of base stations; determining, by the processor, initial deployment solution to obtain initial allocation attributes associated with the pre-requisite number of network resources comprising base stations, wherein determining the initial deployment solution comprises pre-computing a base station (BS) cell design for each feasible base station, wherein the BS cell design comprises at least one coverage attribute associated with the BS; dividing, by the processor, the service area into a plurality of sub-areas based on a Path loss Based Clustering Approach, wherein each of the plurality of sub-areas is serviced by at least one network resource from a pre-requisite number of network resources, wherein the division of the service area into the plurality of sub-areas is based on distribution of demand nodes within the service area, wherein each demand node corresponds to a pre-determined number of users on the communication network, wherein the number of network resources for servicing at least one sub-area is based on user preference or computation time requirement for network resource allocation; iteratively determining, by the processor, a locally optimal deployment solution, comprising at least one local allocation attribute for the at least one network resource in each of the plurality of sub-areas, by utilizing local threshold values corresponding to the one or more of the plurality of objectives to meet the one or more objectives for network resource optimization, wherein the locally optimal deployment solution is iteratively determined based on the local threshold values, wherein the local threshold values correspond to the initial local deployment solution and local deployment solutions obtained in each iteration, wherein the initial local deployment solution and each local deployment solution correspond to a base station (BS) deployment solution; obtaining, by applying a joint optimization technique, by the processor, a globally optimal deployment solution, comprising at least one global allocation attribute for allocation of the pre-requisite number of network resources in the service area, based on the iterative processing of the locally optimal deployment solution to meet the plurality of objectives, wherein the globally optimal deployment solution is obtained by iteratively processing the locally optimal deployment solution based on at least one of an existing traffic patterns, an estimated traffic patterns, and pragmatic network conditions in the service area in order to meet the one or more objectives.