Optimization of fed-batch fermentation processes with bio-inspired algorithms

Rocha, Miguel; Mendes, Rui; Rocha, Orlando; Rocha, Isabel; Ferreira, Eugénio C.

doi:10.1016/j.eswa.2013.09.017

Cited by 49 publications

(28 citation statements)

References 42 publications

(45 reference statements)

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“…The authors of [8] developed an approach of embedded Markov chain model to analyze the signaling cost for movement-based location management (MBLM) scheme in cellular network, and it is applicable for 4G and LTE network. Now, researchers have found that a nature-inspired system is also applicable in communication networks [11,21]. The working of nature-based networking is not limited to ant system, bee system, swarm intelligence, etc.…”

Section: Related Workmentioning

confidence: 99%

Artificial immune system (AIS)-based location management scheme in mobile cellular networks

Biswash

Sarkar

Sharma³

2018

Iran J Comput Sci

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In this paper, we are proposing a bio-inspired location management (LM) technique for personal communication system (PSC). It is based on artificial immune system (AIS), with self-adaptation and self-update attributes to perform the location management, and helps to achieve better quality of service (QoS) and quality of experience (QoE) for the mobile users. Here, we are suggesting a modified mobile switching center (MSC) architecture, and an adaptive self-modified location management procedure. The proposed mobile switching center architecture has an advantage of rule-based and fact-based system to store the rules and facts related to location management procedure, and it shows the intelligent behavior of system. The mobile switching center calculates the best method for location management and the rule-based system trigged the rules to perform the techniques. The system stores the result (techniques for location management) in fact-based system for future use. The efficiency and effectiveness of the proposed techniques have been analyzed, and it observed that the proposed system has 45-50% improvement in performance over the current location management techniques. Here, we are using performance parameters such as signaling cost, database update cost, overhead measurement, and mobility management cost.

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Section: Related Workmentioning

confidence: 99%

Artificial immune system (AIS)-based location management scheme in mobile cellular networks

Biswash

Sarkar

Sharma³

2018

Iran J Comput Sci

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“…This model has been used as a benchmark tool for in silico ethanol production optimization, as presented in the works of several authors such as Banga et al Ochoa, Rocha et al [14,15,18], among others.…”

Section: Fermentation Modelingmentioning

confidence: 99%

“…In this sense, several works presented models for bioenergy production processes through microbial activity, including biohydrogen generation [23][24][25], biogas (used directly, or refined as biomethane) production through anaerobic digestion [26][27][28], bioethanol production (through the biological conversion of sugar-containing crops, amilaceous raw inputs or lignocellulosic materials) [6,18,29], this latter subject appearing as the focal point of the present work.…”

Section: Fermentation Modelingmentioning

confidence: 99%

“…Under a process engineering aspect, the optimization of biotechnological processes aims in its productivity enhancement to exploit the maximum capabilities of an already selected microorganism and by manipulating environmental and operational variables [18], as in order to ensure the improvement of a fed-batch culture yield of a desired product, the concentration of the substrate must be controlled to a proper level. This control is fundamental to avoid the occurrence of overflow metabolism and increasing the cell productivity [33][34][35].…”

Section: Fermentation Modelingmentioning

confidence: 99%

“…The already described complex behavior of the bioprocesses in the process control scope constitutes a non-trivial dynamic optimization problem, necessitating the use of robust techniques capable of find a viable solution that lead to an optimal productivity and a non-local optima entrapment, as well as subject to a reasonable computational effort demand. In this sense, the evolutionary computation techniques represent important alternatives, as those methods usually obtain good solutions with modest computation times, although the global optimum can not be guaranteed [18].…”

Section: Introductionmentioning

confidence: 99%

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Optimization of Bioethanol In Silico Production Process in a Fed-Batch Bioreactor Using Non-Linear Model Predictive Control and Evolutionary Computation Techniques

Freitas

Olivo²,

Andrade³

2017

Energies

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Due to growing worldwide energy demand, the search for diversification of the energy matrix stands out as an important research topic. Bioethanol represents a notable alternative of renewable and environmental-friendly energy sources extracted from biomass, the bioenergy. Thus, the assurance of optimal growth conditions in the fermenter through operational variables manipulation is cardinal for the maximization of the ethanol production process yield. The current work focuses in the determination of optimal control scheme for the fermenter feed rate and batch end-time, evaluating different parametrization profiles, and comparing evolutionary computation techniques, the genetic algorithm (GA) and differential evolution (DE), using a dynamic real-time optimization (DRTO) approach for the in silico ethanol production optimization. The DRTO was able to optimize the reactor feed rate considering disturbances in the process input. Open-loop tests results obtained for the algorithms were superior to several works presented in the literature. The results indicate that the interaction between the intervals of DRTO cycles and parametrization profile is more significant for the GA, both in terms of ethanol productivity and batch time. In general lines, the present work presents a methodology for control and optimization studies applicable to other bioenergy generation systems.

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Current state and perspectives in modeling and control of human pluripotent stem cell expansion processes in stirred‐tank bioreactors

Galvanauskas

Grincas

Simutis

et al. 2017

Biotechnology Progress

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Implementation of model-based practices for process development, control, automation, standardization, and validation are important factors for therapeutic and industrial applications of human pluripotent stem cells. As robust cultivation strategies for pluripotent stem cell expansion and differentiation have yet to be determined, process development could be enhanced by application of mathematical models and advanced control systems to optimize growth conditions. Therefore, it is important to understand both the potential of possible applications and the apparent limitations of existing mathematical models to improve pluripotent stem cell cultivation technologies. In the present review, the authors focus on these issues as they apply to stem cell expansion processes. © 2017 American Institute of Chemical Engineers Biotechnol. Prog., 33:355-364, 2017.

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Optimization of fed-batch fermentation processes with bio-inspired algorithms

Cited by 49 publications

References 42 publications

Artificial immune system (AIS)-based location management scheme in mobile cellular networks

Artificial immune system (AIS)-based location management scheme in mobile cellular networks

Optimization of Bioethanol In Silico Production Process in a Fed-Batch Bioreactor Using Non-Linear Model Predictive Control and Evolutionary Computation Techniques

Current state and perspectives in modeling and control of human pluripotent stem cell expansion processes in stirred‐tank bioreactors

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