There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

Tables of integrals

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

Particle swarm optimization (PSO) is a heuristic global optimization method, proposed originally by Kennedy and Eberhart in 1995. It is now one of the most commonly used optimization techniques. This survey presented a comprehensive investigation of PSO. On one hand, we provided advances with PSO, including its modifications (including quantum-behaved PSO, bare-bones PSO, chaotic PSO, and fuzzy PSO), population topology (as fully connected, von Neumann, ring, star, random, etc.), hybridization (with genetic algorithm, simulated annealing, Tabu search, artificial immune system, ant colony algorithm, artificial bee colony, differential evolution, harmonic search, and biogeography-based optimization), extensions (to multiobjective, constrained, discrete, and binary optimization), theoretical analysis (parameter selection and tuning, and convergence analysis), and parallel implementation (in multicore, multiprocessor, GPU, and cloud computing forms). On the other hand, we offered a survey on applications of PSO to the following eight fields: electrical and electronic engineering, automation control systems, communication theory, operations research, mechanical engineering, fuel and energy, medicine, chemistry, and biology. It is hoped that this survey would be beneficial for the researchers studying PSO algorithms.

/pdf/a-comprehensive-survey-on-particle-swarm-optimization-1d380v5xx1.pdf

A Comprehensive Survey on Particle Swarm Optimization Algorithm and Its Applications

In nature, the eastern North American monarch population is known for its southward migration during the late summer/autumn from the northern USA and southern Canada to Mexico, covering thousands of miles. By simplifying and idealizing the migration of monarch butterflies, a new kind of nature-inspired metaheuristic algorithm, called monarch butterfly optimization (MBO), a first of its kind, is proposed in this paper. In MBO, all the monarch butterfly individuals are located in two distinct lands, viz. southern Canada and the northern USA (Land 1) and Mexico (Land 2). Accordingly, the positions of the monarch butterflies are updated in two ways. Firstly, the offsprings are generated (position updating) by migration operator, which can be adjusted by the migration ratio. It is followed by tuning the positions for other butterflies by means of butterfly adjusting operator. In order to keep the population unchanged and minimize fitness evaluations, the sum of the newly generated butterflies in these two ways remains equal to the original population. In order to demonstrate the superior performance of the MBO algorithm, a comparative study with five other metaheuristic algorithms through thirty-eight benchmark problems is carried out. The results clearly exhibit the capability of the MBO method toward finding the enhanced function values on most of the benchmark problems with respect to the other five algorithms. Note that the source codes of the proposed MBO algorithm are publicly available at GitHub (
 https://github.com/ggw0122/Monarch-Butterfly-Optimization
 , C++/MATLAB) and MATLAB Central (
 http://www.mathworks.com/matlabcentral/fileexchange/50828-monarch-butterfly-optimization
 , MATLAB).

Monarch butterfly optimization

Optimal design of second generation current conveyor using craziness-based particle swarm optimisation

In this paper, the time domain waveform is approximated for calculation of delay, rise, settling time, damping ratio and natural frequency of a second order RLCG on-chip VLSI interconnect line. It can also be evaluated for multiple interconnect systems but due to harmonics higher order systems are ignored. The model is applied to a single RLCG interconnect line which can also be extended for multi-interconnect systems to analyze crosstalk noise. The model evaluates the performance of a system which is expressed in terms of the transient response due to a unit step input. It is easy to generate and evaluate the delay analytically. A closed form expression for the propagation delay of a CMOS gate driving a distributed RLCG line is introduced. On-chip inductance and conductance are expected to have a profound effect on traditional high performance IC design methodologies. In the proposed model, it is shown that when the value of G is increased, the time at which the rise time, settling time and the time when the steady state condition is reached are all increased. So, for high speed circuits one must increase the value of G so that the steady state condition is reached quickly and it is also shown that with the increase in the value of G the delay will reduce. The simulation results performed in SPICE environment justify the efficacy of the proposed model.

TRANSIENT AND DELAY ANALYSIS FOR ON-CHIP HIGH SPEED VLSI RLCG INTERCONNECTION NETWORK IN 0.18µm TECHNOLOGY

Erosion by water reduces soil quality and hence crop yield. Understanding the response of crop yields to soil erosion is vital in assessing agriculture’s vulnerability to erosion. However, these effects are difficult to quantify. The study presents a quantitative relationship between soil erosion and soil quality and productivity of rainfed wheat (Triticum aestivum) by comparing field plots with different degrees of erosion in some sub-tropical alfisols in the Doon Valley region of India. By comparing the topsoil depth with the reference site as the control, erosion severity was classified into different phases such as slight, moderate, severe, and very severe. A quantitative, weighted additive model was used to evaluate soil quality for different phases of erosion using soil clay content, water holding capacity, soil aggregate, soil organic carbon, pH, CEC, total N, available P, and available K. The synthesis of long-term experimental data revealed that the mean soil erosion rate varied from 5.5 Mg ha−1 yr−1 in slightly eroded plots to 33.4 Mg ha−1 yr−1 in very severely eroded plots. Compared with the reference forest, the soil organic carbon (SOC) declined by 81.4% and water holding capacity by 31% in severely eroded soils. A substantial loss of total N, extractable P, and available K was also observed. Water stable aggregates (WSA) decreased from 86% to 12.6%, and the cation exchange capacity (CEC) from 25 to 12.6 c mol(+) kg−1. The soil quality index was 0.7 in slightly eroded compared with 0.4 in severely eroded soil. Similarly, the sustainable yield index for wheat was 0.9 and 0.6 for slightly and severely eroded soils, respectively. Thus, there is a strong need to identify land management systems that reduce erosion risks, restore eroded soils, and enhance soil quality.

/pdf/impacts-of-soil-erosion-on-soil-quality-and-agricultural-leessi20.pdf

Impacts of Soil Erosion on Soil Quality and Agricultural Sustainability in the North-Western Himalayan Region of India

This paper present the optimization of small- signal parameters for GSDG (Gate Stack Double Gate) MOSFET in deep submicron analogue circuit design. The evolutionary optimization algorithms taken for this study are CRPSO (Craziness-based Particle Swarm Optimization) and ALCPSO (Aging Leader Challenger based PSO). The small-signal parameters like trans-conductance, OFF-state current and different other design parameters of GSDG MOSFET are optimized in the regions of sub-threshold and saturation from the above mentioned evolutionary techniques to achieve the superior electrical performance of the MOSFET in the analogue domain. The results obtained from ALCPSO and CRPSO techniques are much improved as compared with the results of preceding literature and may be considered for the useful device design.

An Evolutionary Approach Based Optimization of Small Signal Parameters for GSDG MOSFET

In this article, the electrical parameters of the Gate Stack Double Gate (GSDG) MOSFET are optimized utilizing the Simplex-Particle Swarm Optimization (Simplex-PSO) algorithm. The electrical parameters like the OFF-state current, transconductance and subthreshold swing have been considered to formulate the overall Cost Function (CF). The overall CF is achieved by the weighted sum approach method. The results attained from the Simplex-PSO are formed to be better than the previous literature.

Durbadal Mandal

Papers

Optimal design of second generation current conveyor using craziness-based particle swarm optimisation

TRANSIENT AND DELAY ANALYSIS FOR ON-CHIP HIGH SPEED VLSI RLCG INTERCONNECTION NETWORK IN 0.18µm TECHNOLOGY

Impacts of Soil Erosion on Soil Quality and Agricultural Sustainability in the North-Western Himalayan Region of India

An Evolutionary Approach Based Optimization of Small Signal Parameters for GSDG MOSFET

Optimization of Electrical Parameters for the Gate Stack Double Gate (GSDG) MOSFET using Simplex-PSO Algorithm