Evolutionary Models Research Articles

Enhancing vaccination strategies for epidemic control through effective lockdown measures

Evolutionary epidemiology models have substantially impacted the study of various infections and prevention methods in the biology field. These models are called Susceptible, Lockdown, Vaccinated, Infected, and Recovered (SLVIR) epidemic dynamics. We explore how human behavior, particularly in the context of disease transmission, is influenced by two intervention strategies: vaccination and lockdown, both of which are grounded in the principles of evolutionary game theory (EGT). This comprehensive study using evolutionary game theory delves into the dynamics of epidemics, explicitly focusing on the transition rate from susceptibility to immunity and susceptibility to lockdown measures. Our research involves a thorough analysis of the structural aspects of the SLVIR epidemic model, which delineates disease-free equilibria to ensure stability in the system. Our investigation supports the notion that implementing lockdown measures effectively reduces the required level of vaccinations to curtail the prevalence of new infections. Furthermore, it highlights that combining both strategies is particularly potent when an epidemic spreads rapidly. In regions where the disease spreads comparatively more, our research demonstrates that lockdown measures are more effective in reducing the spread of the disease than relying solely on vaccines. Through significant numerical simulations, our research illustrates that integrating lockdown measures and efficient vaccination strategies can indirectly lower the risk of infection within the population, provided they are both dependable and affordable. The outcomes reveal a nuanced and beneficial scenario where we examine the interplay between the evolution of vaccination strategies and lockdown measures, assessing their coexistence through indicators of average social payoff.

Evolutionary origin and gradual accumulation with plant evolution of the LACS family

BackgroundLACS (long-chain acyl-CoA synthetase) genes are widespread in organisms and have multiple functions in plants, especially in lipid metabolism. However, the origin and evolutionary dynamics of the LACS gene family remain largely unknown.ResultsHere, we identified 1785 LACS genes in the genomes of 166 diverse plant species and identified the clades (I, II, III, IV, V, VI) of six clades for the LACS gene family of green plants through phylogenetic analysis. Based on the evolutionary history of plant lineages, we found differences in the origins of different clades, with Clade IV originating from chlorophytes and representing the origin of LACS genes in green plants. The structural characteristics of different clades indicate that clade IV is relatively independent, while the relationships between clades (I, II, III) and clades (V, VI) are closer. Dispersed duplication (DSD) and transposed duplication (TRD) are the main forces driving the evolution of plant LACS genes. Network clustering analysis further grouped all LACS genes into six main clusters, with genes within each cluster showing significant co-linearity. Ka/Ks results suggest that LACS family genes underwent purifying selection during evolution. We analyzed the phylogenetic relationships and characteristics of six clades of the LACS gene family to explain the origin, evolutionary history, and phylogenetic relationships of different clades and proposed a hypothetical evolutionary model for the LACS family of genes in plants.ConclusionsOur research provides genome-wide insights into the evolutionary history of the LACS gene family in green plants. These insights lay an important foundation for comprehensive functional characterization in future research.

Genome-wide analysis reveals the contributors to fast molecular evolution of the Chinese hook snout carp (Opsariichthys bidens)

Variations in molecular evolutionary rate have been widely investigated among lineages and genes. However, it remains an open question whether fast rate of molecular evolution is driven by natural selection or random drift, and how the fast rate is linked to metabolic rate. Additionally, previous studies on fast molecular evolution have been largely restricted to concatenated matrix of genes or a few specifically selected genes, but less is known for individual genes at the genome-wide level. Here we addressed these questions using more than 5000 single-copy orthologous (SCO) genes through comparative genomic and phylogenetic analyses among fishes, with a special focus on a newly-sequenced clupeocephalan fish the Chinese hook snout carp Opsariichthys bidens. We showed O. bidens displays significantly higher mean substitution rate and more fast-evolving SCO genes (2172 genes) than most fishes studied here. The rapidly evolving genes are enriched in highly conserved and very basic functions such as translation and ribosome that are critical for biological fitness. We further revealed that ∼25 % of these fast-evolving genes exhibit a constant increase of substitution rate from the common ancestor down to the present, suggesting a neglected but important contribution from ancestral states. Model fitting showed that ∼85 % of fast-evolving genes exclusive to O. bidens and related species follow the adaptive evolutionary model rather than random-drift model, and 7.6 % of fast-evolving genes identified in O. bidens have experienced positive selection, both indicating the reflection of adaptive selection. Finally, metabolic rate was observed to be linked with substitution rate in a gene-specific manner. Overall, our findings reveal fast molecular evolution of SCO genes at genome-wide level in O. bidens, and uncover the evolutionary and ecological contributors to it.

Characteristics of laser induced plasma near a flat gas-liquid interface and its effect on the performance of laser induced breakdown spectroscopy (LIBS) detection

Moving the laser focus to the vicinity of the gas-liquid interface is the key point for many new enhanced and new methods to improve the quality of spectral signals in water Laser induced breakdown spectroscopy (LIBS) detection. Understanding the generation and evolution characteristics of the plasma induced by pulsed laser near the gas–liquid interface is of great significance for the establishment of evolution models and improvement of these new LIBS methods. In this paper, a set of slow horizontal flow auxiliary system is established to provide an ideal flat gas–liquid two-phase interface experimental condition. Experimental research on vertical incidence flat system was conducted using techniques such as time-resolved imaging, plasma characterization diagnosis, and spectral analysis. And the detection capabilities of the system were also tested. The characteristics and mechanisms of LIBS near the gas-liquid two-phase interface were investigated with the laser incident on the sample along the vertical direction. Simulation of the laser beam focusing process and observation of laser beam spot images show that the shift of plasma generation position relative to the focal point results from the refraction of the laser beam entering the solution from the air and the ‘interface effect’ of propagation on the vertical direction. Moreover, the plasma forms only the optical power density surpasses the breakdown threshold. In this work, plasma with smaller size, rounder shape, stronger radiation, higher temperature, and higher density can be produced when the focus position is in the liquid column 0.3 mm away from the upper interface. Simultaneously, for example, the Mg ion line at 285.213 nm, the obtained spectral intensity to signal-to-background ratio reaches the maximum value, and a better spectral signal can be obtained, which is 2–4 times of other positions, and the detection limits of the elements Na, Mg, and Ca also reach the lowest level, with 1.6–2.4 times of the detection limit of other focusing positions for Mg and 1.4–1.7 times for Ca, respectively.

Fluorine Abundances in Local Stellar Populations

We present the first fluorine measurements in 12 normal K giants belonging to the Galactic thin and thick disks using spectra obtained with the Phoenix infrared spectrometer on the 2.1 m telescope at Kitt Peak. Abundances are determined from the (1−0) R9 2.3358 μm feature of the molecule HF. Additionally, sodium abundances are derived in 25 giants in the thin disk, thick disk, and halo using the Na i line at 2.3379 μm. We report fluorine abundances for thin and thick disk stars in the metallicity range −0.7 < [Fe/H] < 0. We add two abundance measurements for stars with [Fe/H] < 0.5 dex, which are at a critical metallicity range to constrain models. We find a larger dispersion in fluorine abundances than sodium abundances despite both species having similar overall uncertainties due to atmospheric parameters, suggesting this dispersion is real and not observational. The dispersion is slightly larger in the thick disk than the thin. The thin and thick disk average [F/Fe] for our sample of stars combined with the literature differ by 0.03 dex. The observations are compared to available chemical evolution models.

Mеsozoic Tectonothermal Evolution of the Zagan Metamorphic Core Complex in Western Transbaikalia: 40Ar/39Ar and FTA Dating

Abstract A model of tectonothermal evolution of the Zagan metamorphic core complex (MCC) based on the new data from 40Ar/39Ar dating of amphibole, mica, and apatite fission-track dating is discussed. A relationship with the long-range impact of processes from the collision of the North China (Amurian–North China) block with the Siberian continent in the Mesozoic era is proposed. The Zagan MСС was formed in the Cretaceous period on the southern flank of a high mountain uplift of Western Transbaikalia, composed of late Paleozoic granitoids of the Angara–Vitim batholith. According to 40Ar/39Ar dating of amphiboles and micas from the mylonite zone, the active development time of the Zagan MCC corresponds to the early Cretaceous epoch (131, 114 Ma). The tectonic exposure of the core from about 15 km to the depths of about 10 km occurred at a rate of tectonic erosion of 0.4–0.3 mm/year as a result of post-collisional extension of the Mongol–Okhotsk orogen. Apatite fission-track dating shows that further exhumation and cooling of the rocks to about 3 km occurred in the lower-upper Cretaceous epoch (112, 87 Ma). The erosional denudation rate was about 0.3 mm/year.MCC- metamorphic core complexes, AFT- apatite fission-track

Evolutionary neural network modeling of the impact of digital technologies on the economic development of regions

Evolutionary neural network modeling of the impact of digital technologies on the economic development of regions

Practical guidance and workflows for identifying fast evolving non-coding genomic elements using PhyloAcc.

Comparative genomics provides ample ways to study genome evolution and its relationship to phenotypic traits. By developing and testing alternate models of evolution throughout a phylogeny, one can estimate rates of molecular evolution along different lineages in a phylogeny and link these rates with observations in extant species, such as convergent phenotypes. Pipelines for such work can help identify when and where genomic changes may be associated with, or possibly influence, phenotypic traits. We recently developed a set of models called PhyloAcc, using a Bayesian framework to estimate rates of nucleotide substitution on different branches a phylogenetic tree and evaluate their association with pre-defined or estimated phenotypic traits PhyloAcc-ST and PhyloAcc-GT both allow users to define a priori a set of target lineages and then compare different models to identify loci accelerating in one or more target lineages. Whereas ST considers only one species tree across all input loci, GT considers alternate topologies for every locus. PhyloAcc-C simultaneously models molecular rates and rates of continuous trait evolution,allowing the user to ask whether the two are associated. Here we describe these models and provide tips and workflows on how to prepare the input data and run PhyloAcc.

Missing Data, Speculative Reading

In this article we use an approach we term “speculative reading” to explore gaps in Sylvia Beach’s lending library records and the Shakespeare and Company Project datasets. We recast the problem of missing data as an opportunity and use a combination of time series forecasting, evolutionary models, and recommendation systems to estimate the extent of missing information and speculatively fill in some gaps. We conclude that the datasets include ninety-three percent of membership activity, ninety-six percent of members, and sixty-four percent to seventy-six percent of the books despite only including twenty-six percent of the borrowing activity. We then treat Ernest Hemingway as a test case for speculative reading: based on Hemingway’s known borrowing and all documented borrowing activity, we generate a list of books he might have borrowed during the years his borrowing is not documented; we then verify and interpret our list against the substantial scholarly record of the books he read and owned.

Game analysis on PPP model operation of abandoned mines ecological restoration under the innovation of central government's reward and punishment system in China.

There is a huge funding gap in the abandoned mines ecological restoration in China. It is of great research value to explore how PPP model can better introduce social capital into the low-profit ecological restoration of abandoned mines. Based on the innovation perspective of the central government's reward and punishment system, this paper constructs an evolutionary game model of "local government-social capital", analyzes the interaction and behavior mechanism of core stakeholders in the operation process of abandoned mines ecological restoration PPP mode, and discusses the influence of evolutionary equilibrium strategy and parameters change on evolutionary strategy under different scenarios by Matlab simulation. The research shows that the abandoned mines ecological restoration needs the support of the central government. When the local government lightly punishes the low-quality service of social capital, the central government needs to pay higher costs to promote all parties to actively participate in the operation and supervision of the PPP project. The revenue and cost of government supervision, the operating subsidy for social capital and the cost saved by social capital in providing bad service are the key factors affecting the evolution of the game between government and social capital. Punishment can effectively spur social capital to keep the contract and operate in the project, but the punishment effect will be ineffective without government supervision. Finally, some suggestions are put forward, such as establishing a long-term supervision mechanism and a reasonable income mechanism for PPP projects, increasing penalties for violations, attracting third parties to reduce supervision costs and strengthening communication between the two parties, so as to make the project take into account the economic performance of social capital and the social welfare of government departments, and achieve dual Pareto improvement.

A Numerical Time Integration Procedure for Secondary Dendrite Arm Spacing in Hyper-Peritectic Steel Alloys

AbstractA numerical time integration procedure for the calculation of the secondary dendrite arm spacing (SDAS) in FeC hyper-peritectic alloys is presented, a preferred group of low-carbon casting steel. The procedure incorporates a three-stage thin arm dissolution model, which is solved at each time step using Newton–Raphson iteration. This is coupled to a coarsening model based on the integral forms of the dissolution model, which are solved using Gaussian quadrature, as well as a growth model for solid fraction evolution. The procedure can easily be embedded into numerical models for solidification, in which the space–time evolution of the SDAS is required for determining the dynamic permeability in the mushy zone. Higher order approximations for both growth and solute concentration evolution can easily be incorporated. Temperature dependence of thermophysical parameters is taken into account using inter-dendritic solidification empirical models, and an alloy-specific peritectic reaction constant is used to determine the isothermal peritectic holding time. The procedure is validated against experimental data presented in literature. Various cases of SDAS as a function of local solidification time, cooling rate and carbon composition are investigated. The method is compared to experimental results of SDAS obtained from test castings of a hyper-peritectic steel alloy and can be used to iteratively determine the alloy-specific peritectic reaction constant by comparing the solid fraction evolution during the peritectic reaction with that found from the experimental cooling curve.

Selection leads to false inferences of introgression using popular methods.

Detecting introgression between closely related populations or species is a fundamental objective in evolutionary biology. Existing methods for detecting migration and inferring migration rates from population genetic data often assume a neutral model of evolution. Growing evidence of the pervasive impact of selection on large portions of the genome across diverse taxa suggests that this assumption is unrealistic in most empirical systems. Further, ignoring selection has previously been shown to negatively impact demographic inferences (e.g., of population size histories). However, the impacts of biologically realistic selection on inferences of migration remain poorly explored. Here, we simulate data under models of background selection, selective sweeps, balancing selection, and adaptive introgression. We show that ignoring selection sometimes leads to false inferences of migration in popularly used methods that rely on the site frequency spectrum (SFS). Specifically, balancing selection and some models of background selection result in the rejection of isolation-only models in favor of isolation-with-migration models and lead to elevated estimates of migration rates. BPP, a method that analyzes sequence data directly, showed false positives for all conditions at recent divergence times, but balancing selection also led to false positives at medium divergence times. Our results suggest that such methods may be unreliable in some empirical systems, such that new methods that are robust to selection need to be developed.

Evolution of a stellar system in the context of the virial equation

The virial equation is used to clarify the nature of the dynamic evolution of a stellar system. The methods used are based on analytical and numerical modeling of evolution, as well as on an approach long used in the nonlinear theory of oscillations. It is shown that the mean harmonic radius of a system with negative total energy never exceeds two times the equilibrium value. The time to reach the virial equlibrium state Tv is about two to three dozen dynamic time periods Td. For systems not in close proximity to virial equilibrium, the virial ratio, the mean harmonic radius, and the root mean square radius of the system fluctuate during Tv; then the virial ratio and mean harmonic radius stabilize near their equilibrium values, while the root mean square radius continues to increase (possibly ad infinitum). Thus, the moment of inertia of the system relative to the center of gravity and its potential energy have significantly different behavior, which leads to the formation of a relatively small quasi-equilibrium core and an extended halo.

Estimating mutation rates under heterogeneous stress responses.

Exposure to environmental stressors, including certain antibiotics, induces stress responses in bacteria. Some of these responses increase mutagenesis and thus potentially accelerate resistance evolution. Many studies report increased mutation rates under stress, often using the standard experimental approach of fluctuation assays. However, single-cell studies have revealed that many stress responses are heterogeneously expressed in bacterial populations, which existing estimation methods have not yet addressed. We develop a population dynamic model that considers heterogeneous stress responses (subpopulations of cells with the response off or on) that impact both mutation rate and cell division rate, inspired by the DNA-damage response in Escherichia coli (SOS response). We derive the mutant count distribution arising in fluctuation assays under this model and then implement maximum likelihood estimation of the mutation-rate increase specifically associated with the expression of the stress response. Using simulated mutant count data, we show that our inference method allows for accurate and precise estimation of the mutation-rate increase, provided that this increase is sufficiently large and the induction of the response also reduces the division rate. Moreover, we find that in many cases, either heterogeneity in stress responses or mutant fitness costs could explain similar patterns in fluctuation assay data, suggesting that separate experiments would be required to identify the true underlying process. In cases where stress responses and mutation rates are heterogeneous, current methods still correctly infer the effective increase in population mean mutation rate, but we provide a novel method to infer distinct stress-induced mutation rates, which could be important for parameterising evolutionary models.

Study on triaxial compression performance and damage characteristics of fiber-reinforced ecological matrix cementing gangue gypsum fill material.

Polypropylene fiber was equally mixed into alkali-activated slag fly ash geopolymer in order to ensure the filling effect of mine goaf and improve the stability of cemented gangue paste filling material with ecological matrix. Triaxial compression tests were then conducted under various conditions. The mechanical properties and damage characteristics of composite paste filling materials are studied, and the damage evolution model of paste filling materials under triaxial compression is established, based on the deviatoric stress-strain curve generated by the progressive failure behavior of samples. Internal physical and chemical mechanisms of the evolution of structure and characteristics are elucidated and comprehended via the use of SEM-EDS and XRD micro-techniques. The results show that the fiber can effectively improve the ultimate strength and the corresponding effective stress strength index of the sample within the scope of the experimental study. The best strengthening effect is achieved when the amount of NaOH is 3% of the mass of the solid material, the amount of fiber is 5‰ of the mass of the solid material, and the length of the fiber is about 12 mm. The action mode of the fiber in the sample is mainly divided into single-grip anchoring and three-dimensional mesh traction. As the crack initiates and develops, connection occurs in the matrix, where the fiber has an obvious interference and retardation effect on the crack propagation, thereby transforming the brittle failure into a ductile failure and consequently improving the fracture properties of the ecological cementitious coal gangue matrix. The theoretical damage evolution model of a segmented filling body is constructed by taking the initial compaction stage end point as the critical point, and the curve of the damage evolution model of the specimen under different conditions is obtained. The theoretical model is verified by the results from the triaxial compression test. We concluded that the experimental curve is in good agreement with the theoretical curve. Therefore, the established theoretical model has a certain reference value for the analysis and evaluation of the mechanical properties of paste filling materials. The research results can improve the utilization rate of solid waste resources.

Molecular isotopologue measurements toward super star clusters and the relation to their ages in NGC 253 with ALCHEMI

Context. Determining the evolution of the CNO isotopes in the interstellar medium (ISM) of starburst galaxies can yield important constraints on the ages of super star clusters (SSCs), or on other aspects and factors contributing to their evolution, such as the initial mass function (IMF). Due to the time-dependent nature of the abundances of isotopes within the ISM – as they are supplied from processes such as nucleosynthesis or chemical fractionation –, this provides the opportunity to test whether or not isotope ratios trace the ages of highly star-forming regions, such as SSCs. Aims. The goal of this study is to investigate whether the isotopic variations in SSC regions within NGC 253 are correlated with their different ages as derived from stellar population modelling. Methods. We measured abundance ratios of CO, HCN, and HCO+ isotopologues in six regions containing SSCs within NGC 253 using high-spatial-resolution (1.6″, ∼28 pc) data from the ALCHEMI (ALma Comprehensive High-resolution Extragalactic Molecular Inventory) ALMA Large program. We then analysed these ratios using RADEX radiative transfer modelling, with the parameter space sampled using the nested sampling Monte Carlo algorithm MLFriends. These abundance ratios were then compared to ages predicted in each region via the fitting of observed star-formation tracers (such as Brγ) to Starburst99 starburst stellar population evolution models. Results. We determined the isotopic column density ratios across multiple regions of SSC activity in NGC 253 using non-LTE radiative transfer modelling. We do not find any significant trend with age for the CO and HCN isotopologue ratios on timescales of the ages of the SSC* regions observed. However, HCO+ may show a correlation with age over these timescales in 12C/13C. Conclusions. The driving factors of these ratios within SSCs could be the IMF or fractionation effects. To further probe these effects in SSCs over time, a larger sample of SSCs must be observed spanning a larger age range.

Drivers of genomic differentiation landscapes in populations of disparate ecological and geographical settings within mainland Apis cerana.

Elucidating the evolutionary processes that drive population divergence can enhance our understanding of the early stages of speciation and inform conservation management decisions. The honeybee Apis cerana displays extensive population divergence, providing an informative natural system for exploring these processes. The mainland lineage A. cerana includes several peripheral subspecies with disparate ecological and geographical settings radiated from a central ancestor. Under this evolutionary framework, we can explore the patterns of genome differentiation and the evolutionary models that explain them. We can also elucidate the contribution of non-genomic spatiotemporal mechanisms (extrinsic features) and genomic mechanisms (intrinsic features) that influence these genomic differentiation landscapes. Based on 293 whole genomes, a small part of the genome is highly differentiated between central-peripheral subspecies pairs, while low and partial parallelism partly reflects idiosyncratic responses to environmental differences. Combined elements of recurrent selection and speciation-with-gene-flow models generate the heterogeneous genome landscapes. These elements weight differently between central-island and other central-peripheral subspecies pairs, influenced by glacial cycles superimposed on different geomorphologies. Although local recombination rates exert a significant influence on patterns of genomic differentiation, it is unlikely that low-recombination rates regions were generated by structural variation. In conclusion, complex factors including geographical isolation, divergent ecological selection and non-uniform genome features have acted concertedly in the evolution of reproductive barriers that could reduce gene flow in part of the genome and facilitate the persistence of distinct populations within mainland lineage of A. cerana.

Research on the Evolution Models and Risk of Disaster-Induced Storage Tank Explosions in a Smart City

An important goal of smart cities is to ensure city safety and reduce city risks. However, because the chemical industry park is often located interior and surroundings of a city, it is easy to induce explosions in case of natural disasters, causing serious losses. To investigate the possibility of explosion damage to other storage tanks in chemical industrial parks caused by tank explosions, the evolution process of tank explosion damage was studied, and an analysis method to determine the most unfavorable process was provided. This method is based on regional grid division and shock wave overpressure calculation to obtain the probability of damage at the grid location. Based on the system fault evolution process, the space fault network model was used to calculate the explosion damage evolution process of each storage tank, and the most unfavorable situation was finally determined. The paper assumes a positive linear relationship between the damage probability of the affected storage tank and the likelihood of explosion. The paper provides a calculation method for regional grid division, tank explosion overpressure, and damage probability. A mathematical model for the evolution process of tank explosion damage was constructed, and it is believed that the damage effects of tanks are a logical superposition. The results can provide a reference for controlling the explosion process in chemical industrial parks under the most unfavorable conditions and realize intelligent analysis and prediction of regional risks.

The Centralized Meal Service Delivery Mode

Meal delivery with high delivery timeliness requirements in demand-intensive areas often leads to several issues such as chaotic terminal management and low efficiency during peak times, reducing consumer satisfaction and increasing complaints. This study constructs a dynamic model of meal delivery systems to analyse the operational models and centralized dispatching modes in Guangzhou University City, and applies an evolutionary game model to explore the decisions from the perspectives of government, meal suppliers, riders, and consumers. The study analyses how centralized dispatching mode affects the performance of delivery systems and its impact on the willingness of government, merchants, and riders to participate. The results indicate that demand-intensive areas, centralized dispatching modes have sustainable advantages in terms of cost and efficiency. The effectiveness is closely related to the intensity of government intervention (supervision and support), but weakly related to the timing of intervention. Consumer preferences, shaped by consumer type and perceived value, affect the benefits of participating in a centralized dispatch mode, but not the willingness of meal suppliers to participate. The evolutionary framework in this study provides valuable references for the quantitative evaluation of the meal delivery system, theoretical support for the decision-making of the participants of the meal delivery system, and a research framework for the relevant decision-making scenarios, so as to optimize the allocation of meal resources and promote the sustainable development of meal delivery.

Improved dragonfly optimization algorithm based on quantum behavior for multi-objective optimization of ethylene cracking furnace

Ethylene is one of the important basic raw materials for the modern chemical production, accounting for over 75 % of petrochemical products. And the ethylene cracking furnace is subject to coking problems that can impede the thermal conductivity of the reaction tube. Therefore, an improved multi-objective dragonfly optimization algorithm based on quantum behavior is proposed. The particle evolutionary model introduces the quantum bound state δ-potential well model, which improves the global convergence ability and the convergence speed of the dragonfly optimization algorithm. In addition, the calculation formulas for parameters are improved by introducing natural logarithm and the iterative search method is changed to a triple search. Moreover, the global convergence and local search ability of the quantum behavior enhancement algorithm is assisted by adaptively selecting the search strategy according to the current number of iterations of the improved dragonfly algorithm. Compared with other multi-objective optimization algorithms on the ZDT and CEC test functions, the proposed algorithm has good global convergence and local search capabilities in terms of the inverted general distance. Finally, the proposed algorithm is applied in the multi-objective optimization of an ethylene cracking furnace, with the ethylene yield and the propylene yield as optimization objectives. The experimental results show that the ethylene yield can be increased by 1.5498 %, while the propylene yield decreases by only 0.0081 %, which proves that the proposed algorithm achieves better effect in optimizing the main product yield under fixed cycle adjustment operating conditions compared to original operating conditions.