ADSautomated design synthesis AIs artificial intelligence solutions a i lengths of the longer edge of Obj i b i lengths of the shorter edge of Obj i BLX blend crossover operator CCEF co-operative co-evolutionary framework CCGA co-operative co-evolutionary genetic algorithm C the large constant C 1 , C 2 , ..., C k the normalising coefficients of each sub-objective function CCEF name co-operative co-evolutionary framework C i = {P i ,R i } the permissible location area of the ith object C max1 the big positive numbers to ensure that the value of the (C max1 -T p ) is larger than zero C max2 the big positive numbers to ensure that the value of the (C max2 -NObj) is larger than zero CR ∈ [0,1] a cross factor D the feasible region of variable X DE differential evolution ABSTRACTThe layout design of a satellite module is a complex mechanical layout problem. Its main difficulties lie in combinatorial explosion of computational complexity, engineering complexity, and applicability in engineering practice. Inspired by the human-computer cooperation ideas, a human-computer co-operative co-evolutionary method for optimising layout design of a satellite module is developed. This method constructs the diversity reference set by using the diversity intelligence solutions (DIs) that are created by using the combinatorial operators of differential evolution (DE) and the blend crossover operator (BLX-a). During the co-evolution process of the presented method, the AIs, the DIs and the algorithm solutions are expressed by unified encoding strings and incorporated together to create new co-operative solutions. An instance of a satellite module layout design is presented to demonstrate the feasibility and effectiveness of the proposed method. Compared with the co-evolutionary approach and the all-at-once optimisation approaches, computational results show that the proposed method not only can produce better solutions, but also can better balance the conflicting objectives on the trade-off issues.