Wireless sensor networks (WSNs) has recently drawn lots of attention due to its application in multiple domains. The sensors have limited power sources and in many applications they cannot be recharged or replaced due to hostile nature of the environment. Finding near optimal solutions for the energy problem is still an issue in WSNs. A new era is opened with algorithms inspired by nature to solve optimization problems. In this paper, we propose genetic algorithm based approaches for clustering and routing in WSNs. The objective of this mechanism is to prolong lifetime of a sensor and increase the quality of service. We perform extensive simulations of the proposed algorithms and compare the simulation results with that of the existing algorithms. The results demonstrate that the proposed algorithms outperform the existing algorithms in terms of various performance metrics including energy consumption and number of packets received by the base station.