A Biased Random Key Heuristic Genetic Approach for the Payload Packing Design of A Satellite Module

Existing heuristic evolutionary approaches are effective to solve the multi-module satellite packing problem. But for them, payload allocation and packing optimization are achieved in two different stages. And for their heuristics there are faults of weaker generality and less candidate location. So, a biased random key heuristic genetic approach is proposed for the collaborative payload allocation and packing for multi-module satellite (MSRKHGA). The firstly, by coding and decoding the random key individual and using GA operator, the organic combination of the payload allocation and packing optimization is achieved. Secondly, by region-positioning it can avoid the time-consuming overlapping calculation between individuals and dynamically generate more candidate regions for payloads to be packed. Numerical experiments show that all index of the proposed MSRKHGA approach are superior obviously to those of existing approaches.