This work deals with a problem incorporating two well-known problems: the 3D Bin-packing problem (3D-BPP), and the Knapsack problem. Given the complexity of the problem a hybrid Genetic Algorithm (GA) methodology combining the Deepest Bottom Left Fill (DBLF) heuristics within the GA is presented. The research compares between two methods a basic genetic algorithm based on combining a penalty procedure and the hybrid method. In both cases constraints and various weights are assigned for different characteristics of the 3D packages. Different simulations were tested to find the best GA parameters influencing the convergence of the solutions. The resulted parameters were used when simulating for different number of populations sizes, mutations and number of generations. The hybrid approach achieved much better results by generating satisfying permutation sequences, which improves the efficiency of the 3D packing layouts and maximizing the overall value.

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