RELIABILITY-BASED MULTI-OBJECTIVE OPTIMIZATION APPLIED TO CHEMICAL ENGINEERING DESIGN

ABSTRACT Chemical engineering optimization represents a significant challenge due to the complexity of the mathematical models that are frequently required in this area. These models are normally associated with nonlinear equations that represent mass, energy, and momentum balances, which are submitted to physical, constitutive, environmental, and design limitations. The design of chemical systems is generally carried out by considering the model, the vector of design variables, and system parameters as deterministic values, i.e., small variations in these quantities do not affect the objective function. In this contribution, a new methodology based on a double loop iteration process to evaluate the influence of uncertainties on chemical engineering design is proposed. The inner optimization loop is used to find the solution associated with the highest probability value by using the so-called Inverse Reliability Analysis and the outer loop is the regular optimization loop used to determine the vector of design variables. For this aim, the Multi-Objective Optimization Water Cycle Algorithm is improved, adopting a mechanism of neighborhood exploration. For illustration purposes, the proposed methodology is applied to mathematical functions and to chemical engineering design. The obtained results demonstrate that the proposed strategy represents an interesting alternative to reliability design in chemical engineering.

摘要 化工优化是一项重大挑战，因该领域常用的数学模型具有极高复杂性。这类模型通常关联用于描述质量、能量与动量衡算的非线性方程，需满足物理、本构、环境及设计约束。传统化工系统设计通常将模型、设计变量向量与系统参数视为确定性数值，即默认这些量的微小波动不会对目标函数产生影响。本研究提出一种基于双循环迭代流程的新方法，用于评估不确定性对化工设计的影响：内层优化循环借助所谓的逆可靠性分析（Inverse Reliability Analysis）求解概率值最高的解，外层循环则为常规优化循环，用于确定设计变量向量。为此，本研究对多目标优化水循环算法（Multi-Objective Optimization Water Cycle Algorithm）进行改进，引入邻域探索机制。为便于验证与说明，将所提方法应用于数学函数与化工设计场景。实验结果表明，所提策略为化工领域的可靠性设计提供了一种颇具价值的备选方案。