Differential evolution (DE) is arguably one of the most powerful stochastic real-parameter optimization algorithms in current use. DE operates through similar computational steps as employed by a standard evolutionary algorithm (EA). However, unlike traditional EAs, the DE-variants perturb the current-generation population members with the scaled differences of randomly selected and distinct population members. Therefore, no separate probability distribution has to be used for generating the offspring. Since its inception in 1995, DE has drawn the attention of many researchers all over the world resulting in a lot of variants of the basic algorithm with improved performance. This paper presents a detailed review of the basic concepts of DE and a survey of its major variants, its application to multiobjective, constrained, large scale, and uncertain optimization problems, and the theoretical studies conducted on DE so far. Also, it provides an overview of the significant engineering applications that have benefited from the powerful nature of DE.

/pdf/differential-evolution-a-survey-of-the-state-of-the-art-3lz840pz2t.pdf

Differential Evolution: A Survey of the State-of-the-Art

Numerical Initial Value Problems in Ordinary Differential Equations

In this review, we summarize the knowledge of the production and properties of charcoal that has been accumulated over the past 38 millenia. The manipulation of pressure, moisture content, and gas flow enables biomass carbonization with fixed-carbon yields that approachor attainthe theoretical limit after reaction times of a few tens of minutes. Much of the heat needed to carbonize the feed is released by vigorous, exothermic secondary reactions that reduce the formation of unwanted tars by augmenting the charcoal yield in a well-designed carbonizer. As a renewable fuel, charcoal has many attractive features:  it contains virtually no sulfur or mercury and is low in nitrogen and ash; it is highly reactive yet easy to store and handle. Carbonized charcoal can be a good adsorbent with a large surface area and a semimetal with an electrical resistivity comparable to that of graphite. Recent advances in knowledge about the production and properties of charcoal presage its expanded use as a renewable fuel, red...

/pdf/the-art-science-and-technology-of-charcoal-production-2yxzbuvb7k.pdf

The Art, Science, and Technology of Charcoal Production†

Differential Evolution (DE) is arguably one of the most powerful and versatile evolutionary optimizers for the continuous parameter spaces in recent times. Almost 5 years have passed since the first comprehensive survey article was published on DE by Das and Suganthan in 2011. Several developments have been reported on various aspects of the algorithm in these 5 years and the research on and with DE have now reached an impressive state. Considering the huge progress of research with DE and its applications in diverse domains of science and technology, we find that it is a high time to provide a critical review of the latest literatures published and also to point out some important future avenues of research. The purpose of this paper is to summarize and organize the information on these current developments on DE. Beginning with a comprehensive foundation of the basic DE family of algorithms, we proceed through the recent proposals on parameter adaptation of DE, DE-based single-objective global optimizers, DE adopted for various optimization scenarios including constrained, large-scale, multi-objective, multi-modal and dynamic optimization, hybridization of DE with other optimizers, and also the multi-faceted literature on applications of DE. The paper also presents a dozen of interesting open problems and future research issues on DE.

Recent advances in differential evolution – An updated survey

A nonlinear model predictive controller has been developed to maintain normoglycemia in subjects with type 1 diabetes during fasting conditions such as during overnight fast. The controller employs a compartment model, which represents the glucoregulatory system and includes submodels representing absorption of subcutaneously administered short-acting insulin Lispro and gut absorption. The controller uses Bayesian parameter estimation to determine time-varying model parameters. Moving target trajectory facilitates slow, controlled normalization of elevated glucose levels and faster normalization of low glucose values. The predictive capabilities of the model have been evaluated using data from 15 clinical experiments in subjects with type 1 diabetes. The experiments employed intravenous glucose sampling (every 15 min) and subcutaneous infusion of insulin Lispro by insulin pump (modified also every 15 min). The model gave glucose predictions with a mean square error proportionally related to the prediction horizon with the value of 0.2 mmol L(-1) per 15 min. The assessment of clinical utility of model-based glucose predictions using Clarke error grid analysis gave 95% of values in zone A and the remaining 5% of values in zone B for glucose predictions up to 60 min (n = 1674). In conclusion, adaptive nonlinear model predictive control is promising for the control of glucose concentration during fasting conditions in subjects with type 1 diabetes.

/pdf/nonlinear-model-predictive-control-of-glucose-concentration-2l5wkss7wi.pdf

Nonlinear model predictive control of glucose concentration in subjects with type 1 diabetes

Thermal cracking of hydrocarbons in the presence of steam is the most important process for the production of ethylene and propylene, which are the raw materials for many petrochemicals In this work, multiobjective optimization (MOO) of an industrial LPG (liquefied petroleum gas containing mainly propane and butane) thermal cracker is studied using the elitist nondominated sorting genetic algorithm adapted with the jumping gene operator, NSGA-II-aJG A first principles model based on free radical mechanism for LPG thermal cracking is employed for optimization Several bi- and triobjective optimization problems are solved; these problems involved maximization of annual ethylene/propylene production, selectivity and run length, and minimization of severity and total heat duty per year Feed flow rate, steam ratio, inlet temperature, coil outlet temperature, and pressure are the decision variables MOO of the LPG thermal cracker provides a range of optimal operating conditions and objective values, with the triobjective optimization giving more optimal solutions compared to those from the biobjective optimization for the objectives considered With this detailed knowledge, a suitable operating point can be selected based on specific requirements in the particular plant

Multiobjective Optimization of an Industrial LPG Thermal Cracker using a First Principles Model

A study of finding many desirable solutions in multiobjective optimization of chemical processes

Performance analysis of plantwide control (PWC) systems, which is one of the important areas of PWC of industrial processes, has not received much attention in the past. In this paper, many measures based on plant dynamics are described and discussed for evaluating the performance of different control structures in the presence of disturbances. These include overall process settling time, dynamic disturbance sensitivity, the total variation in the plant manipulated variables, net variation from the nominal profit, deviation from the production rate target, and the integral absolute error in product purity. These measures are developed and then applied to four alternative control structures of an important industrial process, namely, styrene monomer plant, in order to test their applicability. The results indicate that some of the presented measures are indeed effective in evaluating and comparing different PWC structures. The most important contribution of this paper is the presentation of some clear and ...

Gade Pandu Rangaiah

Papers

Multiobjective Optimization of an Industrial LPG Thermal Cracker using a First Principles Model

A study of finding many desirable solutions in multiobjective optimization of chemical processes

Criteria for Performance Assessment of Plantwide Control Systems

Modeling and analysis of solid catalyzed reactive HiGee stripping

Closed-loop tuning of process control systems