The main focus of this paper is to present thermodynamic and economic analyses and multi-objective optimization of a novel geothermal-solar multigeneration system. The system aims to produce hydrogen, freshwater, electricity, cooling load, and hot water and designed based on geothermal and solar energy. After modeling and thermodynamic and economic analysis, exergy destruction rate, exergy efficiency and, cost rate were calculated for each component of the system. The results showed that the highest amount of exergy destruction was related to parabolic trough collectors (PTCs) and absorption chillers. To select the geothermal fluid of the organic Rankine cycle (ORC), several different fluids were investigated, among which isobutene was selected. By using the Group method of data handling (GMDH) neural network, a mathematical relationship was obtained between the inputs and outputs of the problem and were given as inputs to the non-dominated sorting genetic algorithm II (NSGAII)alg. The final optimal point was obtained applying the tech- nique for order of preference by similarity to ideal solution (TOPSIS) decision criterion at which the exergy efficiency and cost rate were calculated to be 21.63% and 63.89 $/h, respectively. The meteorological data of the Zanjan, Isfahan, and Bandar Abbas cities were used to calculate the performance accurately at the TOPSIS selection point. To provide a comparison between different cities, the performance of the system was evaluated on September 17 as a sample day. On this day, the proposed system produces 26.38 kg of hydrogen and 373.8 m(3) of freshwater in Isfahan. (C) 2020 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.