Search results for: optimization and searching paths.

Authors: Ramin Javadzadeh, Zahra Afsahi, MohammadReza Meybodi

Abstract:

The hybridization of artificial immune system with cellular automata (CA-AIS) is a novel method. In this hybrid model, the cellular automaton within each cell deploys the artificial immune system algorithm under optimization context in order to increase its fitness by using its neighbor-s efforts. The hybrid model CA-AIS is introduced to fix the standard artificial immune system-s weaknesses. The credibility of the proposed approach is evaluated by simulations and it shows that the proposed approach achieves better results compared to standard artificial immune system.

Keywords: Artificial Immune System, Cellular Automat, neighborhood

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Authors: K. Divya, G. Sugumaran

Abstract:

This paper proposes an improved Maximum Power Point Tracking of PhotoVoltaic system using Deterministic Partical Swarm Optimization technique. This method has the ability to track the maximum power under varying environmental conditions i.e. partial shading conditions. The advantage of this method, particles moves in the restricted value of velocity to achieve the maximum power. SEPIC converter is employed to boost up the voltage of PV system. To estimate the value of the proposed method, MATLAB simulation carried out under partial shading condition.

Keywords: DPSO, Partial shading condition, P&O, PV, SEPIC.

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Authors: M.J. Park, K.H. Kim, O.M. Kwon

Abstract:

This paper proposes a delay-dependent leader-following consensus condition of multi-agent systems with both communication delay and probabilistic self-delay. The proposed methods employ a suitable piecewise Lyapunov-Krasovskii functional and the average dwell time approach. New consensus criterion for the systems are established in terms of linear matrix inequalities (LMIs) which can be easily solved by various effective optimization algorithms. Numerical example showed that the proposed method is effective.

Keywords: Multi-agent systems, probabilistic self-delay, consensus, Lyapunov method, LMI.

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Authors: Alessio Mastrorillo, Giuseppe Silvi, Francesco Scagliola

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This paper explores the decoding of Ambisonics material into 2-channel mixing formats, addressing challenges related to stereo speakers and headphones. We present the Universal HJ (UHJ) format as a solution, enabling the preservation of the entire horizontal plane and offering versatile spatial audio experiences. Our paper presents a UHJ format decoder, explaining its design, computational aspects, and empirical optimization. We discuss the advantages of UHJ decoding, potential applications, and its significance in music composition. Additionally, we highlight the integration of this decoder within the Envelop for Live (E4L) suite.

Keywords: Ambisonics, UHJ, quadrature filter, virtual reality, Gerzon, decoder, stereo, binaural, biquad.

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Authors: Tommaso Adamo, Gianpaolo Ghiani, Antonio D. Grieco, Emanuela Guerriero

Abstract:

Batch production plants provide a wide range of scheduling problems. In pharmaceutical industries a batch process is usually described by a recipe, consisting of an ordering of tasks to produce the desired product. In this research work we focused on pharmaceutical production processes requiring the culture of a microorganism population (i.e. bacteria, yeasts or antibiotics). Several sources of uncertainty may influence the yield of the culture processes, including (i) low performance and quality of the cultured microorganism population or (ii) microbial contamination. For these reasons, robustness is a valuable property for the considered application context. In particular, a robust schedule will not collapse immediately when a cell of microorganisms has to be thrown away due to a microbial contamination. Indeed, a robust schedule should change locally in small proportions and the overall performance measure (i.e. makespan, lateness) should change a little if at all. In this research work we formulated a constraint programming optimization (COP) model for the robust planning of antibiotics production. We developed a discrete-time model with a multi-criteria objective, ordering the different criteria and performing a lexicographic optimization. A feasible solution of the proposed COP model is a schedule of a given set of tasks onto available resources. The schedule has to satisfy tasks precedence constraints, resource capacity constraints and time constraints. In particular time constraints model tasks duedates and resource availability time windows constraints. To improve the schedule robustness, we modeled the concept of (a, b) super-solutions, where (a, b) are input parameters of the COP model. An (a, b) super-solution is one in which if a variables (i.e. the completion times of a culture tasks) lose their values (i.e. cultures are contaminated), the solution can be repaired by assigning these variables values with a new values (i.e. the completion times of a backup culture tasks) and at most b other variables (i.e. delaying the completion of at most b other tasks). The efficiency and applicability of the proposed model is demonstrated by solving instances taken from a real-life pharmaceutical company. Computational results showed that the determined super-solutions are near-optimal.

Keywords: Constraint programming, super-solutions, robust scheduling, batch process, pharmaceutical industries.

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Authors: Bo Bae Song, Byung Seok Lee, Hyun Young Kim, Chung Kwang Lee, Yong Seo Koo

Abstract:

This paper proposed a silicon controller rectifier (SCR) based ESD protection device to protect low voltage ESD for integrated circuit. The proposed ESD protection device has low trigger voltage and high holding voltage compared with conventional SCR-based ESD protection devices. The proposed ESD protection circuit is verified and compared by TCAD simulation. This paper verified effective low voltage ESD characteristics with low trigger voltage of 5.79V and high holding voltage of 3.5V through optimization depending on design variables (D1, D2, D3 and D4).

Keywords: ESD, SCR, Holding voltage, Latch-up.

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Authors: Bipul Krishna Saha, Basab Chakraborty, Ashish Alex Sam, Parthasarathi Ghosh

Abstract:

The demand for energy is cumulatively increasing with time.  Since the availability of conventional energy resources is dying out gradually, significant interest is being laid on searching for alternate energy resources and minimizing the wastage of energy in various fields.  In such perspective, low-grade waste heat from several industrial sources can be reused to generate electricity. The present work is to further the adoption of the Organic Rankine Cycle (ORC) technology in Indian industrial sector.  The present paper focuses on extending the previously reported idea to the next level through a comparative review with three different working fluids using practical data from an Indian industrial plant. For comprehensive study in the simulation platform of Aspen Hysys^®, v8.6, the waste heat data has been collected from a current coke oven gas plant in India.  A parametric analysis of non-regenerative ORC and regenerative ORC is executed using the working fluids R-123, R-11 and R-21 for subcritical ORC system.  The primary goal is to determine the optimal working fluid considering various system parameters like turbine work output, obtained system efficiency, irreversibility rate and second law efficiency under applied multiple heat source temperature (160 °C- 180 °C).  Selection of the turbo-expanders is one of the most crucial tasks for low-temperature applications in ORC system. The present work is an attempt to make suitable recommendation for the appropriate configuration of the turbine. In a nutshell, this study justifies the proficiency of integrating the ORC technology in Indian perspective and also finds the appropriate parameter of all components integrated in ORC system for building up an ORC prototype.

Keywords: Organic rankine cycle, regenerative organic rankine cycle, waste heat recovery, Indian industry.

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Authors: Seung Pil Pack

Abstract:

Carbonic anhydrases (CAs) has been focused as biological catalysis for CO2 sequestration process because it can catalyze the conversion of CO2 to bicarbonate. Here, codon-optimized sequence of α type-CA cloned from Duneliala species. (DsCAopt) was constructed, expressed, and characterized. The expression level in E. coli BL21(DE3) was better for codon-optimized DsCAopt than intact sequence of DsCAopt. DsCAopt enzyme shows high-stability at pH 7.6/10.0. In final, we demonstrated that in the Ca2+ solution, DsCAopt enzyme can catalyze well the conversion of CO2 to CaCO3, as the calcite form.

Keywords: Carbonic anhydrase, Codon-optimization, Duneliala species, CO2 sequestration

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Authors: Nadezhda Nikolaeva, Tatyana Alexandrova, Alexandr Alexandrov

Abstract:

Processing of high-silicon bauxite on the base of the traditional clinkering method is related to high power consumption and capital investments, which makes production of alumina from those ores non-competitive in terms of basic economic showings. For these reasons, development of technological solutions enabling to process bauxites with various chemical and mineralogical structures efficiently with low level of thermal power consumption is important. Flow sheet of the studies on washability of ores from the Timanskoe and the Severo-Onezhskoe deposits is on the base of the flotation method.

Keywords: Low-quality bauxite, resource-saving technology, optimization, aluminum, conditioning of composition, separation characteristics.

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Authors: Ilqar Ramazanli

Abstract:

The matrix completion problem has been studied broadly under many underlying conditions. In many real-life scenarios, we could expect elements from distinct columns or distinct positions to have a different cost. In this paper, we explore this generalization under adaptive conditions. We approach the problem under two different cost models. The first one is that entries from different columns have different observation costs, but, within the same column, each entry has a uniform cost. The second one is any two entry has different observation cost, despite being the same or different columns. We provide complexity analysis of our algorithms and provide tightness guarantees.

Keywords: Matrix completion, adaptive learning, heterogeneous cost, Matroid optimization.

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Authors: Hidehiko Okada

Abstract:

The author proposes an extension of genetic algorithm (GA) for solving fuzzy-valued optimization problems. In the proposed GA, values in the genotypes are not real numbers but fuzzy numbers. Evolutionary processes in GA are extended so that GA can handle genotype instances with fuzzy numbers. The proposed method is applied to evolving neural networks with fuzzy weights and biases. Experimental results showed that fuzzy neural networks evolved by the fuzzy GA could model hidden target fuzzy functions well despite the fact that no training data was explicitly provided.

Keywords: Evolutionary algorithm, genetic algorithm, fuzzy number, neural network, neuroevolution.

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Authors: S. Swain, P. S. Khuntia

Abstract:

In this paper an optimal convex controller is designed to control the angle of attack of a FOXTROT aircraft. Then the order of the system model is reduced to a low-dimensional state space by using Balanced Truncation Model Reduction Technique and finally the robust stability of the reduced model of the system is tested graphically by using Kharitonov rectangle and Zero Exclusion Principle for a particular range of perturbation value. The same robust stability is tested theoretically by using Frequency Sweeping Function for robust stability.

Keywords: Convex Optimization, Kharitonov Stability Criterion, Model Reduction, Robust Stability.

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Authors: A. Bocevska, G. Todorov, T. Neshkov

Abstract:

New developed approach for Functional Cost Analysis (FCA) based on virtual prototyping (VP) models in CAD/CAE environment, applicable and necessary in developing new products is presented. It is instrument for improving the value of the product while maintaining costs and/or reducing the costs of the product without reducing value. Five broad classes of VP methods are identified. Efficient use of prototypes in FCA is a vital activity that can make the difference between successful and unsuccessful entry of new products into the competitive word market. Successful realization of this approach is illustrated for a specific example using press joint power tool.

Keywords: CAD/CAE environment, Functional Cost Analysis (FCA), Virtual prototyping (VP) models.

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Authors: S. Ramana Babu, V. Ramachandra Raju, K. Ramji

Abstract:

This paper presents the effect of actuation schemes on the performance of parallel manipulators and also how the singularity loci have been changed in the reachable workspace of the manipulator with the choice of actuation scheme to drive the manipulator. The performance of the eight possible actuation schemes of 3RRR planar parallel manipulator is compared with each other. The optimal design problem is formulated to find the manipulator geometry that maximizes the singularity free conditioned workspace for all the eight actuation cases, the optimization problem is solved by using genetic algorithms.

Keywords: Actuation schemes, GCI, genetic algorithms.

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Authors: Refaat M Mohamed, Ayman El-Baz, Aly A. Farag

Abstract:

This paper presents a new approach for the prob-ability density function estimation using the Support Vector Ma-chines (SVM) and the Expectation Maximization (EM) algorithms.In the proposed approach, an advanced algorithm for the SVM den-sity estimation which incorporates the Mean Field theory in the learning process is used. Instead of using ad-hoc values for the para-meters of the kernel function which is used by the SVM algorithm,the proposed approach uses the EM algorithm for an automatic optimization of the kernel. Experimental evaluation using simulated data set shows encouraging results.

Keywords: Density Estimation, SVM, Learning Algorithms, Parameters Estimation.

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Authors: Chadlia Jerad, Amel Grissa-Touzi, Habib Ounelli

Abstract:

Negation is useful in the majority of the real world applications. However, its introduction leads to semantic and canonical problems. SEPN nets are well adapted extension of predicate nets for the definition and manipulation of stratified programs. This formalism is characterized by two main contributions. The first concerns the management of the whole class of stratified programs. The second contribution is related to usual operations optimization (maximal stratification, incremental updates ...). We propose, in this paper, useful algorithms for manipulating stratified programs using SEPN. These algorithms were implemented and validated with STRPRO tool.

Keywords: stratified programs, update operations, SEPN formalism, algorithms, STRPRO.

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Authors: Tayeb Lardjane, Rabah Messaci

Abstract:

We consider a network of two M/M/1 parallel queues having the same poisonnian arrival stream with rate λ. Upon his arrival to the system a customer heads to the shortest queue and stays until being served. If the two queues have the same length, an arriving customer chooses one of the two queues with the same probability. Each duration of service in the two queues is an exponential random variable with rate μ and no jockeying is permitted between the two queues. A new numerical method, based on linear programming and convex optimization, is performed for the computation of the steady state solution of the system.

Keywords: Steady state solution, matrix formulation, convex set, shortest queue, linear programming.

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Authors: Amer Al Mahmoud Alsheikh, Jan Žídek, František Krčma

Abstract:

Using ab initio theoretical calculations, we present analysis of fragmentation process. The analysis is performed in two steps. The first step is calculation of fragmentation energies by ab initio calculations. The second step is application of the energies to kinetic description of process. The energies of fragments are presented in this paper. The kinetics of fragmentation process can be described by numerical models. The method for kinetic analysis is described in this paper. The result - composition of fragmentation products - will be calculated in future. The results from model can be compared to the concentrations of fragments from mass spectrum.

Keywords: Ab initio, Density functional theory, Fragmentation energy, Geometry optimization.

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Authors: Barıs Kocer, Ahmet Arslan

Abstract:

Travelling salesman problem (TSP) is a combinational optimization problem and solution approaches have been applied many real world problems. Pure TSP assumes the cities to visit are fixed in time and thus solutions are created to find shortest path according to these point. But some of the points are canceled to visit in time. If the problem is not time crucial it is not important to determine new routing plan but if the points are changing rapidly and time is necessary do decide a new route plan a new approach should be applied in such cases. We developed a route plan transfer method based on transfer learning and we achieved high performance against determining a new model from scratch in every change.

Keywords: genetic algorithms, transfer learning, travellingsalesman problem

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Authors: Qingqing Wang, Baocheng Chen, Shouming Zhong

Abstract:

In this paper, the problem of stability criteria for Markovian jumping BAM neural networks with leakage and discrete delays has been investigated. Some new sufficient condition are derived based on a novel Lyapunov-Krasovskii functional approach. These new criteria based on delay partitioning idea are proved to be less conservative because free-weighting matrices method and a convex optimization approach are considered. Finally, one numerical example is given to illustrate the the usefulness and feasibility of the proposed main results.

Keywords: Stability, Markovian jumping neural networks, Timevarying delays, Linear matrix inequality.

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Authors: Essam Al Daoud

Abstract:

This study solves a phylogeny problem by using modified wild dog pack optimization. The least squares error is considered as a cost function that needs to be minimized. Therefore, in each iteration, new distance matrices based on the constructed trees are calculated and used to select the alpha dog. To test the suggested algorithm, ten homologous genes are selected and collected from National Center for Biotechnology Information (NCBI) databanks (i.e., 16S, 18S, 28S, Cox 1, ITS1, ITS2, ETS, ATPB, Hsp90, and STN). The data are divided into three categories: 50 taxa, 100 taxa and 500 taxa. The empirical results show that the proposed algorithm is more reliable and accurate than other implemented methods.

Keywords: Least squares, neighbor joining, phylogenetic tree, wild dogpack.

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Authors: Jiashang Jiang, Yongxin Yuan

Abstract:

In this paper we develop an efficient numerical method for the finite-element model updating of damped gyroscopic systems based on incomplete complex modal measured data. It is assumed that the analytical mass and stiffness matrices are correct and only the damping and gyroscopic matrices need to be updated. By solving a constrained optimization problem, the optimal corrected symmetric damping matrix and skew-symmetric gyroscopic matrix complied with the required eigenvalue equation are found under a weighted Frobenius norm sense.

Keywords: Model updating, damped gyroscopic system, partially prescribed spectral information.

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Authors: Hyung Suk Kang

Abstract:

A triangular fin with variable fin base thickness is analyzed and optimized using a two-dimensional analytical method. The influence of fin base height and fin base thickness on the temperature in the fin is listed. For the fixed fin volumes, the maximum heat loss, the corresponding optimum fin effectiveness, fin base height and fin tip length as a function of the fin base thickness, convection characteristic number and dimensionless fin volume are represented. One of the results shows that the optimum heat loss increases whereas the corresponding optimum fin effectiveness decreases with the increase of fin volume.

Keywords: A triangular fin, Convection characteristic number, Heat loss, Fin base thickness.

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Authors: Mohsen Ebrahimi, Milad M. Rabieh

Abstract:

In this paper, two very different optimization algorithms, Genetic and DIRECT algorithms, are used to history match a bottomhole pressure response for a reservoir with wellbore storage and skin with the best possible analytical model. No initial guesses are available for reservoir parameters. The results show that the matching process is much faster and more accurate for DIRECT method in comparison with Genetic algorithm. It is furthermore concluded that the DIRECT algorithm does not need any initial guesses, whereas Genetic algorithm needs to be tuned according to initial guesses.

Keywords: DIRECT algorithm, Genetic algorithm, Analytical modeling, History match

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Authors: Arshia Azam, J. Amarnath, Ch. D. V. Paradesi Rao

Abstract:

The advantage of solving the complex nonlinear problems by utilizing fuzzy logic methodologies is that the experience or expert-s knowledge described as a fuzzy rule base can be directly embedded into the systems for dealing with the problems. The current limitation of appropriate and automated designing of fuzzy controllers are focused in this paper. The structure discovery and parameter adjustment of the Branched T-S fuzzy model is addressed by a hybrid technique of type constrained sparse tree algorithms. The simulation result for different system model is evaluated and the identification error is observed to be minimum.

Keywords: Fuzzy logic, branch T-S fuzzy model, tree modeling, complex nonlinear system.

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Authors: Omar M. Sallabi, Younis El-Haddad

Abstract:

The Genetic Algorithm (GA) is one of the most important methods used to solve many combinatorial optimization problems. Therefore, many researchers have tried to improve the GA by using different methods and operations in order to find the optimal solution within reasonable time. This paper proposes an improved GA (IGA), where the new crossover operation, population reformulates operation, multi mutation operation, partial local optimal mutation operation, and rearrangement operation are used to solve the Traveling Salesman Problem. The proposed IGA was then compared with three GAs, which use different crossover operations and mutations. The results of this comparison show that the IGA can achieve better results for the solutions in a faster time.

Keywords: AI, Genetic algorithms, TSP.

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Authors: P. Luangpaiboon

Abstract:

Various intelligences and inspirations have been adopted into the iterative searching process called as meta-heuristics. They intelligently perform the exploration and exploitation in the solution domain space aiming to efficiently seek near optimal solutions. In this work, the bee algorithm, inspired by the natural foraging behaviour of honey bees, was adapted to find the near optimal solutions of the transportation management system, dynamic multi-zone dispatching. This problem prepares for an uncertainty and changing customers- demand. In striving to remain competitive, transportation system should therefore be flexible in order to cope with the changes of customers- demand in terms of in-bound and outbound goods and technological innovations. To remain higher service level but lower cost management via the minimal imbalance scenario, the rearrangement penalty of the area, in each zone, including time periods are also included. However, the performance of the algorithm depends on the appropriate parameters- setting and need to be determined and analysed before its implementation. BEE parameters are determined through the linear constrained response surface optimisation or LCRSOM and weighted centroid modified simplex methods or WCMSM. Experimental results were analysed in terms of best solutions found so far, mean and standard deviation on the imbalance values including the convergence of the solutions obtained. It was found that the results obtained from the LCRSOM were better than those using the WCMSM. However, the average execution time of experimental run using the LCRSOM was longer than those using the WCMSM. Finally a recommendation of proper level settings of BEE parameters for some selected problem sizes is given as a guideline for future applications.

Keywords: Meta-heuristic, Bee Algorithm, Dynamic Multi-Zone Dispatching, Linear Constrained Response SurfaceOptimisation Method, Weighted Centroid Modified Simplex Method

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Authors: K. Firsanov, S. Gritsutenko, R. Dinis

Abstract:

By employing BS (Base Station) cooperation we can increase substantially the spectral efficiency and capacity of cellular systems. The signals received at each BS are sent to a central unit that performs the separation of the different MT (Mobile Terminal) using the same physical channel. However, we need accurate sampling and quantization of those signals so as to reduce the backhaul communication requirements. In this paper we consider the optimization of the quantizers for BS cooperation systems. Four different quantizer types are analyzed and optimized to allow better SQNR (Signal-to-Quantization Noise Ratio) and BER (Bit Error Rate) performance.

Keywords: Base Stations cooperation scheme, Bit Error Rate (BER), Quantizer, Signal to Quantization Noise Ratio (SQNR), SCFDE.

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Authors: N. Belkhir, A. Chorfa, D. Bouzid

Abstract:

In this work, grinding or microcutting tools in the form of pellets were manufactured using a bounded alumina abrasive grains. The bound used is a vitreous material containing quartz feldspars, kaolinite and a quantity of hematite. The pellets were used in glass grinding process to replace the free abrasive grains lapping process. The study of the elaborated pellets were done to define their effectiveness in the grinding process and to optimize the influence of the pellets elaboration parameters. The obtained results show the existence of an optimal combination of the pellets elaboration parameters for each glass grinding phase (coarse to fine grinding). The final roughness (rms) reached by the elaborated pellets on a BK7 glass surface was about 0.392 μm.

Keywords: Abrasive grain, glass, grinding, pellet.

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Authors: P. Góes, J. Manzi

Abstract:

This paper focuses on the development of an energy efficiency index that will be applied to reactive systems, which is based in the First and Second Law of Thermodynamics, by giving particular consideration to the concept of maximum entropy. Among the requirements of such energy efficiency index, the practical feasibility must be essential. To illustrate the performance of the proposed index, such an index was used as decisive factor of evaluation for the optimization process of an industrial reactor. The results allow the conclusion to be drawn that the energy efficiency index applied to the reactive system is consistent because it extracts the information expected of an efficient indicator, and that it is useful as an analytical tool besides being feasible from a practical standpoint. Furthermore, it has proved to be much simpler to use than tools based on traditional methodologies.

Keywords: Energy efficiency, maximum entropy, reactive systems.

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