A Heuristic Multi-Criteria Optimization Method for Controlling the Benzene Production Process in a Fuzzy Environment

Abstract

In practice, benzene production is carried out in complex technological facilities such as Benzene Production Units (BPUs). These units include several interconnected subsystems of oil refineries, characterized by several interacting operational parameters that affect both the production volume and the quality indicators of the final product. As a result, the control problem is inherently multi-criteria and is further complicated by operational constraints and uncertainty in part of the input information. In this study, the problem of multi-criteria optimization of the benzene production process control under uncertainty is considered. An efficient heuristic optimization method based on fuzzy modeling is proposed for decision-making in a fuzzy environment, which aims at improving production efficiency while taking into account several conflicting criteria. The validation results obtained through simulation using real operational data from the Atyrau Oil Refinery show that, compared with a deterministic baseline method, the proposed approach increases benzene production by 2.1 t/day (approximately 1.6%), while also outperforming the fuzzy Analytic Hierarchy Process (AHP) method. The obtained results confirm the effectiveness of the proposed approach for supporting decision-making in the management of technological processes under uncertainty.