Recently, interest in incorporating distributed generators (DGs) into electrical distribution networks has significantly increased throughout the globe due to the technological advancements that have led to lowering the cost of electricity, reducing power losses, enhancing power system reliability, and improving the voltage profile. These benefits can be maximized if the optimal allocation and sizing of DGs into a radial distribution system (RDS) are properly designed and developed. Getting the optimal location and size of DG units to be installed into an existing RDS depends on the various constraints, which are sometimes overlapping or contradicting. In the last decade, meta-heuristic search and optimization algorithms have been frequently developed to handle the constraints and obtain the optimal DG location and size. This paper proposes an efficient optimization technique to optimally allocate multiple DG units into a RDS. The proposed optimization method considers the integration of solar photovoltaic (PV) based DG units in power distribution networks. It is based on multi-objective function (MOF) that aims to maximize the net saving level (NSL), voltage deviation level (VDL), active power loss level (APLL), environmental pollution reduction level (EPRL), and short circuit level (SCL). The proposed algorithms using various strategies of inertia weight particle swarm optimization (PSO) are applied on the standard IEEE 69-bus system and a real 205-bus Algerian distribution system. The proposed approach and design of such a complicated multi-objective functions are ultimately to make considerable improvements in the technical, economic, and environmental aspects of power distribution networks. It was found that EIW-PSO is the best applied algorithm as it achieves the maximum targets on various quantities; it gives 75.8359%, 28.9642%, and 64.2829% for the APLL, EPRL, and VDL, respectively, with DG units’ installation in the IEEE 69-bus test system. For the same number of DG units, EIW-PSO gives remarkable improved performance with the Adrar City 205-bus test system; numerically, it shows 72.3080%, 22.2027%, and 63.6963% for the APLL, EPRL, and VDL, respectively. The simulation results of this study prove that the proposed algorithms exhibit higher capability and efficiency in fixing the optimum DG settings.