A New Multi/Many-Objective Optimization Approach in Wireless Sensor Networks for E-commerce Applications

The optimization of Wireless Sensor Networks (WSNs) is critical in the ever-changing environment of E-commerce. This work describes a unique technique for designing and modelling energy-efficient WSNs adapted to the specific demands of E-commerce applications. This study investigates the complex connection between network performance, data collection, and energy saving using cutting-edge AI and optimization approaches. The suggested Multi/Many-optimization algorithm tries to establish a delicate balance by providing smooth data transmission and collection under E-commerce circumstances while minimising energy usage through the incorporation of intelligence algorithms. This research contributes to the advancement of operational efficiency and sustainability within the E-commerce business. The fundamental goal of this research is to discover the Pareto-optimal front in Multi/Many-objective optimization, that contains the subtle trade-offs between 2-objectives and 3-objectives. This allows decision-makers to compare the frequently contradictory objectives of WSN networks. The suggested technique, which is recognised for its adaptability, variety, and multi-objective optimization capabilities, prepares the way for the full potential of E-commerce applications and services.