A production planning benchmark for real-world refinery-petrochemical complexes

TL;DR

The paper tackles the lack of reproducible, industry-relevant benchmarks for integrated refinery-petrochemical planning by introducing an open-source, demand-driven benchmark built on a novel port-stream hybrid superstructure and delta-base modeling for key units. It provides three real-world cases with fully accessible parameters, enabling multi-period planning that accounts for inventories, capacities, and complex material networks. Computational results reveal current global MINLP solvers struggle on industrial-scale networks, while ablation studies show delta-base modeling significantly improves feasibility and yield realism. The benchmark offers a platform for developing tighter relaxations, decomposition methods, and uncertainty-management techniques to advance enterprise-wide optimization in refinery-petrochemical complexes.

Abstract

To achieve digital intelligence transformation and carbon neutrality, effective production planning is crucial for integrated refinery-petrochemical complexes. Modern refinery planning relies on advanced optimization techniques, whose development requires reproducible benchmark problems. However, existing benchmarks lack practical context or impose oversimplified assumptions, limiting their applicability to enterprise-wide optimization. To bridge the substantial gap between theoretical research and industrial applications, this paper introduces the first open-source, demand-driven benchmark for industrial-scale refinery-petrochemical complexes with transparent model formulations and comprehensive input parameters. The benchmark incorporates a novel port-stream hybrid superstructure for modular modeling and broad generalizability. Key secondary processing units are represented using the delta-base approach grounded in historical data. Three real-world cases have been constructed to encompass distinct scenario characteristics, respectively addressing (1) a stand-alone refinery without integer variables, (2) chemical site integration with inventory-related integer variables, and (3) multi-period planning. All model parameters are fully accessible. Additionally, this paper provides an analysis of computational performance, ablation experiments on delta-base modeling, and application scenarios for the proposed benchmark.

Figures (7)

• Figure 1: Key sets and variables to define a process network using different superstructures
• Figure 2: A simplified flowchart of an integrated refinery-petrochemical complex
• Figure 3: Illustration of port-stream superstructure
• Figure 4: General unit model for batch material balance
• Figure 5: Illustration of the delayed coking process