Wireless Sensor Network (WSN) design for intruder detection application requires the decision of deployment of nodes with respect to the lifetime of the network. Based on literature survey it is found that few works have been made on optimizing both decision variables for maximizing the network coverage and lifetime. But the above two objectives in the latter studies are considered individually without any application specific. In this work, it is defined as the multi-objective Deployment and Power Assignment Problem (DPAP) for intruder detection application is solved using Multi Objective Evolutionary Algorithm (MOEA) based on decomposition. The M-tour Selection (M-tourS), Adaptive crossover and Adaptive mutation are introduced to improve the MOEA/D algorithm. The DPAP decomposed into a set of sub problems that are classified based on the above proposed genetic operators into seven different combinations. The proposed operators adapt to the requirements and objective preferences of each combination dynamically during the evolution, resulting in significant improvements on the overall performance of MOEA/D. Simulation parameters are fixed by considering the above application specific. The results show that the proposed algorithm significantly better than the existing algorithms in different network instances.