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In this paper, we present three novel approaches that are based on nature inspired metaheuristics to solve the Multiple-choice Multidimensional Knapsack Problem (MMKP). The first appraoch depends on the procedures of Genetic Algorithm (GA) and is called GAMMKP. The second approach depends on the procedures of Artificial Immune System (AIS) and is called AISMMKF. The third is the hybrid intelligent approach and is called EQAMMKP. The HAMMKF enhanced the performance of the Honey Bees Mating Optimization (HBMO) algorithm by adding some improvements to its components using the possibilities and capabilities of GAMMKP and AISMMKP approaches. Furthermore, we carry out a comparative analysis among these approaches according to three evaluation criteria (quality of solution, computation time, and memory usage) to investigate the performance and determine the capabilities of each novel approach to solve MMKP.