In our previous paper, we proposed a novel combinatorial auction (CA) based cloud market model for trading services that allows cloud providers (CPs) to make groups and submit their bids collaboratively as a single bid for winning the auction. But to find a good combination of CP partners and make groups is a NP-hard problem. Since each provider only has limited information about other providers, past collaborative task information (i.e. no. of times collaboratively win the auctions, failed to make groups, etc.) needs to be analyzed and utilized for partner selection. We call it multi-task and multi-objective optimization problem. To solve this problem, in this paper, we propose a hybrid algorithm that utilizes artificial neural network (ANN) for gathering and analyzing information about previous tasks and then uses multi-objective genetic algorithm (MOGA) to solve the partner selection problem. Simulation results show that our proposed algorithm is effective.