Multi-objective optimisation using evolutionary algorithms constitutes a powerful computational framework that addresses complex problems involving conflicting objectives. By emulating natural ...

In this optimization model, each solution determines the value of C i for all components. Since a solution should contain the sequence of multiple operations of multiple components, it has to be ...

This multi-granularity representation enhances global search efficiency and accelerates convergence. MGO outperforms many popular state-of-the-art algorithms in the CEC2013 single-objective ...

In the algorithm performance test, it is better than MOSSA algorithm, NSGAII algorithm and MOPSO algorithm, and can better solve the multi-objective optimization problem. 2) The multi-objective ...

Co-optimizing air temperature (AT) and CO2 concentration (CO2) for AIoT systems in controlled environment agriculture (CEA) has raised sustained attentions to balance energy efficiency and crop ...