Simplified symbolic transfer function factorization using combined artificial bee colony and simulated annealing

Shokouhifar, Mohammad; Jalali, Ali

doi:10.1016/j.asoc.2017.02.029

Cited by 23 publications

(18 citation statements)

References 31 publications

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“…Therefore, the proposed sustainable coal supply chain combined with the ecological impact aspects is also a NP-hard problem. The available techniques for NP-hard problems can be classified into exact, heuristic, and metaheuristic methods [30]. Exact algorithms (e.g., branch & bound) are guaranteed to find an optimal solution.…”

Section: Solution Methods Based On Genetic Algorithmmentioning

confidence: 99%

Sustainable Coal Supply Chain Management Using Exergy Analysis and Genetic Algorithm

Naderi

Nikabadi

Alem-Tabriz

et al. 2020

Management Systems in Production Engineering

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Environmental threats of coal usage in the electricity production combined with the consumption of renewable and non-renewable resources had led to worldwide energy challenges. The cost of coal mining and economical and environmentally sustainable usage of mined coal could be optimized by efficient management of coal supply chain. This paper provides a mathematical model for improving coal supply chain sustainability including the cost of exergy destruction (entropy). In the proposed method, exergy analysis is used to formulate the model considering not only economic costs but also destructed exergy cost, while genetic algorithm is applied to efficiently solve the proposed model. In order to validate the proposed methodology, some numerical examples of coal supply chains are presented and discussed to show the usability of the proposed exergetic coal supply chain model and claim its benefits over the existing models. According to the results, the proposed method provides 17.6% saving in the consumed exergy by accepting 2.7% more economic costs. The presented model can be used to improve the sustainability of coal supply chain for either designing new projects or upgrading existing processes.

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Section: Solution Methods Based On Genetic Algorithmmentioning

confidence: 99%

Sustainable Coal Supply Chain Management Using Exergy Analysis and Genetic Algorithm

Naderi

Nikabadi

Alem-Tabriz

et al. 2020

Management Systems in Production Engineering

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“…8 illustrates the structure of the low-voltage folded-cascode OTA simulated in this section. It is a single-stage fully-differential topology with one dominant pole at the output node, which results in a GBW relation similar to (10). The target design specification is to maintain GBW = 2π × 1 MHz for C L = 1.2 pF, when the input and output common-mode voltages are set…”

Section: Design Examplesmentioning

confidence: 99%

“…The p MOS devices,

M_{1}

and

M_{2}

are working in strong inversion as current mirror, whereas the n MOS devices are operating in weak inversion to support the

I_{PTAT}

expression. We, therefore, start the sizing sequence by choosing a

g_{m} / I_{D}

range of [10–14] and [22–25] for the p MOS and n MOS devices, respectively, in line with the sizing commands listed in Fig. 11.…”

Section: Design Examplesmentioning

confidence: 99%

“…The multi-dimensional nature of circuit behaviour promotes the application of evolutionary algorithms for the design and synthesis of the ICs. Several design methodologies are therefore proposed, including the use of genetic algorithm (GA) [5], genetic programming [6], non-dominated sorting GA (NSGA-II) [7,8], simulated annealing [9,10], geometric programming [11], imperialist competitive algorithm [12] etc. [13,14] for sizing of the integrated components.…”

Section: Introductionmentioning

confidence: 99%

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Systematic circuit design and analysis using generalised g _m / I _D functions of MOS devices

Aminzadeh

2020

IET Circuits, Devices & Systems

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The conventional approach to implementing analogue integrated circuits in nano-scale complementary metal oxide semiconductor (CMOS) technologies relies basically on circuit simulations using the SPICE models provided by the foundries. Depending on the circuit complexity, the designer should, however, spend a significant amount of time sizing the metal oxide semiconductor field effect transistors such that maximum efficiency is achieved for minimum power consumption and silicon area. Analytical-based design procedures can assist the designer in confronting the sizing challenge of the metal oxide semiconductor (MOS) devices. The procedures are, however, dependent on circuit topology, model parameters, and device physics. This study aims at presenting a systematic approach for analysis and design of analogue circuits in scaled CMOS. For this purpose, the behaviour of short-channel MOS devices is characterised in various process and temperature corners using an updated matrix representation of different device scales, bias conditions, and small-signal parameters. The details to effectively extract the matrix derivation of the technology model files are presented, enabling to devise generalised functions for the design and analysis of the circuits. The design examples include a 0.39 V-28 µA reference circuit, and a 7.50 µA/V operationaltransconductance amplifier with 1.0 V voltage supply in 90-nm CMOS.

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“…These improvements can basically be considered under two main groups; the first is the hybridization with the other algorithms, the second is to develop a new search strategy or to improve the existing search strategies [17,18]. Some of the hybrid methods based on the ABC algorithm are Differential Evolution (DE) [19], Neuro-Fuzzy System [20], Extended Genetic Programming [21], Particle Swarm Optimization algorithm [22], Harmony Search Algorithm [23], Simulated Annealing algorithm [24], Quantum Evolutional Algorithm [25], Bacterial foraging optimization algorithm [26], search strategy [27].…”

Section: Introductionmentioning

confidence: 99%

An enhanced artificial bee colony algorithm based on fitness weighted search strategy

Çelik

2021

Automatika

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Artificial Bee Colony (ABC) algorithm is a meta-heuristic algorithm, is inspired by the bee's food search behaviour based on swarm intelligence. Successful applications were performed on many optimization problems using this algorithm rising in popularity over the past few years. The update mechanism of the ABC algorithm, despite the fact that its exploration is good, faces the problem of convergence performance. For solving convergence problem of ABC Algorithm An Artificial Bee Colony Algorithm Based Fitness Weighted Search (ABCFWS) algorithm proposed in this paper. In this approach, an intelligent search space is proposed instead of the random search space of the ABC algorithm. In this method, the fitness values of the food source and the selected neighbour food source are taken as weights and a more balanced search space was found in the direction of the food source with better fitness value. The proposed method has been applied to 28 unconstrained numerical optimization test problems with different characteristics and the results were compared with the ABC algorithm variations. The results show that the proposed method is successful and competitive.

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Simplified symbolic transfer function factorization using combined artificial bee colony and simulated annealing

Cited by 23 publications

References 31 publications

Sustainable Coal Supply Chain Management Using Exergy Analysis and Genetic Algorithm

Sustainable Coal Supply Chain Management Using Exergy Analysis and Genetic Algorithm

Systematic circuit design and analysis using generalised g _m / I _D functions of MOS devices

An enhanced artificial bee colony algorithm based on fitness weighted search strategy

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Simplified symbolic transfer function factorization using combined artificial bee colony and simulated annealing

Cited by 23 publications

References 31 publications

Sustainable Coal Supply Chain Management Using Exergy Analysis and Genetic Algorithm

Sustainable Coal Supply Chain Management Using Exergy Analysis and Genetic Algorithm

Systematic circuit design and analysis using generalised g m / I D functions of MOS devices

An enhanced artificial bee colony algorithm based on fitness weighted search strategy

Contact Info

Product

Resources

About

Systematic circuit design and analysis using generalised g _m / I _D functions of MOS devices