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Cellular architecture, energy efficiency, and self‐optimizing network are key features to meet the forecast requirements of the fifth‐generation networks. Frequently, the major optimization focus is on maximizing the data rate, but many other objectives are considered ahead to be optimized in the standardization of green fifth‐generation networks such as ubiquitous coverage, cost, availability, latency, automation, energy efficiency, load balancing, mobility, and awareness, which are often conflicting objectives. In this paper, we propose a multiobjective evolutionary framework using a real traffic profile and three‐dimensional beamforming to ensure green self‐optimization of the network cellular layouts. The framework is based on a genetic algorithm (GA) handling conflicting objectives: coverage, capacity, energy efficiency, load balancing, and mobility. The simulation results show a dynamic and automated design of the network layouts following the spatial and temporal fluctuation of the traffic. The sectors are switched‐on, shaped, and switched‐off only where and when required for both macro and virtual small cell layers.

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