Unmanned aerial vehicle (UAV) communications and networks are of utmost concern. However, they have challenges such as the limited on-board energy and restricted transmit power. In this paper, we study a UAV-enabled communication scenario that a set of UAVs perform a virtual antenna array (VAA) to communicate with different remote base stations (BSs) by using collaborative beamforming (CB). To achieve a better transmission performance, the UAV elements can fly to optimal positions by using optimal speeds and adjust to optimal excitation current weights for performing CB transmissions. However, there are some trade-offs between energy consumption and transmission performance. Thus, we formulate a time and energy minimization communication multi-objective optimization problem (TEMCMOP) of CB in UAV networks to simultaneously minimize the total transmission time, total performing time of VAAs and total motion and hovering energy consumptions of UAVs by jointly optimizing the positions, flight speeds and excitation current weights of UAVs, as well as the order of communicating with different BSs. Due to the complexity and NP-hardness of the formulated TEMCMOP, we propose an improved multi-objective ant lion optimization (IMOALO) algorithm with chaos-opposition based learning solution initialization and hybrid solution update operators to solve the problem. Simulation results verify that the proposed IMOALO can effectively solve the formulated TEMCMOP and it has better performance than some other benchmark approaches.