Load growth puts pressure on existing electric infrastructure and impacts on the system's performance parameters which may necessitate network expansion. Conventionally, electric network expansion is done by building new substations or reinforcing the existing ones with new transformers and upgrading the network feeders. However, optimal allocation of combined heat and power distributed generators (CHP-DGs) on distribution networks (DNs) can be adopted for network expansion planning problem. Optimal DG allocation is an optimisation problem which requires an efficient optimisation approach. In this paper, an improved particle swarm optimisation (IPSO) based on weighted randomised acceleration coefficient and adaptive inertia weight is proposed for optimal DG allocation problem. The considered CHP-DGs include internal combustion engine (ICE) and fuel cells (FCs) powered by biogas obtained from anaerobic digestion of food wastes. The proposed IPSO is tested on IEEE 69 bus radial distribution network under single and multi-objectives considering constant and mixed seasonal voltage-dependent load models. Some of the key findings show that integrating ICE-based CHP-DGs operating at optimal power factor in winter day mixed voltage dependent load in base year achieves 97.63 % active power loss reduction in comparison to 77.14 % loss reduction for unity power factor operating FC-based CHP-DG. Economic and environmental evaluation indicate that FC-based CHP-DG records a net present value of over 29.29 million $, levelised cost of energy of 0.0493 $/kWh and zero pollutant emission in comparison with 28.40 million $, 0.0501 $/kWh and 0.2817 million kg pollutant emission for ICE-based CHP-DG over the planning horizon. In comparison with the standard PSO, the proposed IPSO performs better in terms of solution quality, convergence speed and statistical results.