Scheduling and heat integration of multi-product plant based on genetic algorithm

doi:10.1016/j.cjche.2025.05.029

摘要/Abstract

摘要： The research on scheduling and heat integration of batch process plays an important role in reducing energy consumption, improving production efficiency and enhancing the competitiveness of industries. The complexity and difficulty of the model solving are increased due to the comprehensive consideration of both scheduling and heat integration. In this paper, the mixed integer nonlinear programming (MINLP) mathematical model of multi-product plant heat integration optimization with the goal of energy-saving annual profit (EAP) is established. The simultaneous optimization and sequential optimization are carried out respectively by bi-level programming (BP) based on the genetic algorithm (GA), and the calculation results are compared. EAP better captures the trade-off relationship between scheduling schemes, energy-saving profits, and equipment costs. The bi-level programming approach based on GA categorizes variables into integer and real types, enabling structural optimization and parameter optimization of the heat exchanger network. This, in turn, enhances solution efficiency and overcomes the limitations of conventional optimization algorithms in terms of solution speed and quality. Two examples show that the EAP of indirect heat integration considering the storage tank are 21% and 2% higher than that of the direct heat integration, and EAP of the simultaneous optimization are 26% and 6% higher than that of the sequential optimization. The example demonstrates that the model and algorithm are applicable to batch multi-product plants, such as those in the chemical, pharmaceutical, and food industries, and possess strong practicality and innovation.

关键词: Multi-product plant, Heat integration, Scheduling, Genetic algorithm, Heat exchanger network, Bi-level programming

Abstract: The research on scheduling and heat integration of batch process plays an important role in reducing energy consumption, improving production efficiency and enhancing the competitiveness of industries. The complexity and difficulty of the model solving are increased due to the comprehensive consideration of both scheduling and heat integration. In this paper, the mixed integer nonlinear programming (MINLP) mathematical model of multi-product plant heat integration optimization with the goal of energy-saving annual profit (EAP) is established. The simultaneous optimization and sequential optimization are carried out respectively by bi-level programming (BP) based on the genetic algorithm (GA), and the calculation results are compared. EAP better captures the trade-off relationship between scheduling schemes, energy-saving profits, and equipment costs. The bi-level programming approach based on GA categorizes variables into integer and real types, enabling structural optimization and parameter optimization of the heat exchanger network. This, in turn, enhances solution efficiency and overcomes the limitations of conventional optimization algorithms in terms of solution speed and quality. Two examples show that the EAP of indirect heat integration considering the storage tank are 21% and 2% higher than that of the direct heat integration, and EAP of the simultaneous optimization are 26% and 6% higher than that of the sequential optimization. The example demonstrates that the model and algorithm are applicable to batch multi-product plants, such as those in the chemical, pharmaceutical, and food industries, and possess strong practicality and innovation.

Key words: Multi-product plant, Heat integration, Scheduling, Genetic algorithm, Heat exchanger network, Bi-level programming

Ke Li, Lingqi Kong, Xinping Wang, Mengyu Liu. Scheduling and heat integration of multi-product plant based on genetic algorithm[J]. 中国化学工程学报, 2025, 87(11): 115-128.

Ke Li, Lingqi Kong, Xinping Wang, Mengyu Liu. Scheduling and heat integration of multi-product plant based on genetic algorithm[J]. Chinese Journal of Chemical Engineering, 2025, 87(11): 115-128.

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