Catalytic Cracking Multi-Objective Optimization With SPEA2 Guidance

The patent segments the optimization process into multiple independent objective functions (economic benefit, energy consumption, emission reduction) that can be evaluated separately but simultaneously optimized. This segmentation allows the use of multi-objective optimization algorithms to handle each objective independently while finding balanced solutions, thereby improving optimization efficiency and reducing time compared to sequential single-objective approaches.

The patent transforms the multi-objective optimization problem into a parameter optimization problem by defining weighted objective functions that combine multiple goals. By changing the weighting parameters, the system can dynamically adjust the balance between different objectives (economic benefit, energy consumption, emissions), enabling faster convergence and more stable results without requiring multiple separate optimization runs.

The patent implements feedback mechanisms where the results from individual objective evaluations are fed back into the overall optimization process. The algorithm uses feedback from each objective function's evaluation to adjust the search direction and converge faster. This feedback loop prevents the need for large numbers of iterations by continuously refining solutions based on accumulated information from all objectives, reducing computational complexity while maintaining multi-objective capability.

The patent performs preliminary actions by pre-defining the objective functions, constraints, and evaluation criteria before the optimization process begins. This preliminary setup includes establishing the mathematical models for economic benefit, energy consumption, and emission reduction, which guides the optimization algorithm from the start and reduces the number of iterations needed compared to approaches that explore objectives without prior structuring.

The patent creates a universal optimization framework that can handle multiple objectives (economic benefit, energy consumption, emission reduction) within a single integrated system. This multi-functional approach maintains ease of operation by providing a unified interface and process flow, while simultaneously improving reliability by considering all objectives together rather than separately, ensuring comprehensive and reliable optimization results.

The patent combines multiple objective functions into a composite optimization model that integrates economic, energy, and environmental considerations. This composite approach maintains the simplicity of a unified optimization process while enhancing result quality by ensuring that solutions satisfy multiple competing objectives simultaneously, rather than optimizing for a single objective in isolation.