Metaheuristic Methods for Chemical Reactor Design and Process Optimization A Methodological Perspective

Abstract

Chemical reactor and process optimization combines nonlinear models, constraints, mixed design variables and competing engineering objectives. This methodological perspective examines how evolutionary and swarm search can be represented, constrained and evaluated in that setting. It distinguishes algorithm descriptions from evidence of performance, surrogate accuracy from physical validation, and offline design from safety-critical online control. The documentary scope is narrative rather than a verified systematic corpus: the reported screening counts are unreconciled, and the retained generic plots do not establish reactor-specific experimental results. The analysis emphasizes feasibility, matched evaluation budgets, reproducible simulation models, suitable statistical units and explicit trade-offs among production, energy, environmental and safety objectives. It provides criteria for future reactor optimization studies without asserting an optimizer ranking or a complete synthesis of 179 chemical engineering papers.