An Improved Multioperator-Based Constrained Differential Evolution for Optimal Power Allocation in WSNs

Abstract

Optimal power allocation (OPA), which can be transformed into an optimization problem with constraints, plays a key role in wireless sensor networks (WSNs). In this paper, inspired by ant colony optimization, an improved multioperator-based constrained adaptive differential evolution (namely, IMO-CADE) is proposed for the OPA. The proposed IMO-CADE can be featured as follows: (i) to adaptively select the proper operator among different operators, the feedback of operators and the status of individuals are considered simultaneously to assign the selection probability; (ii) the constrained reward assignment is used to measure the feedback of operators; (iii) the parameter adaptation is used for the parameters of differential evolution. To extensively evaluate the performance of IMO-CADE, it is used to solve the OPA for both the independent and correlated observations with different numbers of sensor nodes. Compared with other advanced methods, simulation results clearly indicate that IMO-CADE yields the best performance on the whole. Therefore, IMO-CADE can be an efficient alternative for the OPA of WSNs, especially for WSNs with a large number of sensor nodes.

Solution of Mixed-Integer Optimization Problems in Bioinformatics with Differential Evolution Method

“…Various offspring generation strategies were combined to produce an algorithm with enhanced properties, such as DE with composite strategies and parameters CoDE [65], DE that selects mutation strategies and control parameters from the strategy and parameter pools, respectively, to produce successful offspring population EPSDE [69], the framework with two mechanisms, namely, the multiple variants adaptive selecting mechanism and the multiple variants adaptive solutions preserving mechanisms [70], and improved ensemble of differential evolution variants (IEDEV) [71]. A method with multiple variant coordination was proposed in [72], the archiving of promising directions was suggested [73], and IMO-CADE was introduced in [74], where mutation operators were selected adaptively.…”

Research on Power Control Routing Algorithm for Wireless Sensor Networks Based on Ant Colony Optimization

“…It also increases the network lifetime at the same time. The transmission direction, node residual energy, and distance between nodes were introduced into the ant probability selection and path pheromone update mechanism in the literature [16,17], which presented an ant colony routing optimization algorithm based on adaptive power. This algorithm's advantage is its ability to dynamically modify the transmitting power of the next hop node in accordance with the distance between nodes.…”