检索结果-内蒙古大学图书馆

Well placement optimization using metaheuristic bat algorithm

JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING 2017年 150卷 348-354页

作者： Naderi, Meysam Khamehchi, Ehsan Amirkabir Univ Technol Fac Petr Engn Tehran Polytech Hafez Ave Tehran Iran

The design of an optimal field development and production management is a complicating task because of influencing various factors on decision-making process. Typical factors include number and type of wells, well locations, production constraints, economic factors like capital expenditure, operating costs, and oil sale price. The situation is further complicated due to the uncertainty associated with various effective engineering and geological parameters. In this study, three meta heuristics algorithms of genetic algorithm (GA), particle swarm optimization (PSO) and bat inspired algorithm (BA) are used for optimal determination of six production well locations. Net present value (NPV) is used as an objective function in optimization process. PUNQ-S3 benchmark model is simulated in MATLAB environment in order to search the entire complex reservoir during optimization. Next, the effectiveness of algorithms will be compared in terms of convergence rate and NPV improvement over iterations. The simulation results show that the BA is superior since it reduces the number of functional evaluations and thus improving the computational efficiency. In addition, the BA provides better NPV improvement over PSO and GA. The results indicate that the BA increases NPV by 7.5% and 21.7% over PSO and GA respectively.

关键词： Well placement optimization Net present value Genetic algorithm Particle swarm optimization bat algorithm

来源：评论

学校读者我要写书评

暂无评论

An enhanced bat algorithm approach for reducing electrical power consumption of air conditioning systems based on differential operator

引用

APPLIED THERMAL ENGINEERING 2016年 99卷 834-840页

作者： Coelho, Leandro dos Santos Askarzadeh, Alireza Pontifical Catholic Univ Parana PUCPR Ind & Syst Engn Grad Program PPGEPS Curitiba Parana Brazil Univ Fed Parana Dept Elect Engn BR-80060000 Curitiba Parana Brazil Grad Univ Adv Technol Inst Sci & High Technol & Environm Sci Dept Energy Management & Optimizat Kerman Iran

Energy saving plays a vital role in the decision-making process surrounding building design. Most often, the power consumption of chillers has a significant proportion of the total power consumption of the heating, ventilating and air conditioning (HVAC) systems. The problem of efficiently managing multiple chiller systems (MCSs) in HVAC is complex in many respects. In particular, the electrical energy consumption markedly increases if the machines are not properly managed. In this paper, an extended version of optimal chiller loading (OCL), namely, daily optimal chiller loading (DOCL) is introduced where a 24-h cooling load profile should be satisfied by a number of chillers so that the total power consumption of the chillers during 24-h is minimized. Then, an efficient optimization method is proposed for solving the DOCL by means of a new enhanced differential bat algorithm (DBA) which is a swarm intelligence paradigm. The simulation results represent that DBA produces promising results in comparison with other optimization metaheuristics, such as the original BA, firefly algorithm (FA), harmony search (HS), chicken swarm optimization (CSC), differential evolution (DE) and exponential natural evolution strategy (xNES). (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Multiple chiller systems optimization Electrical power consumption bat algorithm Differential evolution

来源：评论

学校读者我要写书评

暂无评论

Data Clustering Method Based on Improved bat algorithm With Six Convergence Factors and Local Search Operators

引用

IEEE ACCESS 2020年 8卷 80536-80560页

作者： Zhu, L. F. Wang, J. S. Wang, H. Y. Guo, S. S. Guo, M. W. Xie, W. Univ Sci & Technol Liaoning Sch Elect & Informat Engn Anshan 114051 Peoples R China Univ Sci & Technol Liaoning Natl Financial Secur & Syst Equipment Engn Res Ct Anshan 114051 Peoples R China

Clustering as an unsupervised learning method is a process of dividing a data object or observation object into a subset, that is to classify the data through observation learning instead of example learning without the guidance of the prior class label information. bat algorithm (BA) is a swarm intelligence optimization algorithm inspired by bat's ultrasonic echo localization foraging behavior, but it has the disadvantages of being easily trapped into local minima and not being highly accurate. So an improved bat algorithm was proposed. In the global search, a Gaussian-like convergence factor is added, and five different convergence factors are proposed to improve the global optimization ability of the algorithm. In the local search, the hunting mechanism of the whale optimization algorithm (WOA) and the sine position updating strategy are adopted to improve the local optimization ability of the algorithm. This paper compares the clustering effect of the improved bat algorithm with bat algorithm, flower pollination algorithm (FPA), harmony search (HS) algorithm, whale optimization algorithm and particle swarm optimization (PSO) algorithm on seven real data sets under six different convergence factors. The simulation results show that the clustering effect of the improved bat algorithm is superior to other intelligent optimization algorithms.

关键词： Clustering bat algorithm convergence factor hunting mechanism sinusoidal position update strategy

来源：评论

学校读者我要写书评

暂无评论

A self-adaptive bat algorithm for the truck and trailer routing problem

引用

ENGINEERING COMPUTATIONS 2018年第1期35卷 108-135页

作者： Wang, Chao Zhou, Shengchuan Gao, Yang Liu, Chao Beijing Univ Technol Sch Econ & Management Beijing Peoples R China Qingdao Geotech Invest & Surveying Res Inst Qingdao Peoples R China

Purpose The purpose of this paper is to provide an effective solution method for the truck and trailer routing problem (TTRP) which is one of the important NP-hard combinatorial optimization problems owing to its multiple real-world applications. It is a generalization of the famous vehicle routing problem (VRP), involving a group of geographically scattered customers served by the vehicle fleet including trucks and trailers. Design/methodology/approach The meta-heuristic solution approach based on bat algorithm (BA) in which a local search procedure performed by five different neighborhood structures is developed. Moreover, a self-adaptive (SA) tuning strategy to preserve the swarm diversity is implemented. The effectiveness of the proposed SA-BA is investigated by an experiment conducted on 21 benchmark problems that are well known in the literature. Findings Computational results indicate that the proposed SA-BA algorithm is computationally efficient through comparison with other existing algorithms found from the literature according to solution quality. As for the actual computational time, the SA-BA algorithm outperforms others. However, the scaled computational time of the SA-BA algorithm underperforms the other algorithms. Originality/value In this work the authors show that the proposed SA-BA is effective as a method for the TTRP problem. To the authors' knowledge, the BA has not been applied previously, as in this work, to solve the TTRP problem.

关键词： Vehicle routing bat algorithm Self-adaptive Truck and trailer

来源：评论

学校读者我要写书评

暂无评论

Drilling rate of penetration prediction and optimization using response surface methodology and bat algorithm

引用

JOURNAL OF NATURAL GAS SCIENCE AND ENGINEERING 2016年 31卷 829-841页

作者： Moraveji, Mostafa Keshavarz Naderi, Meysam Amirkabir Univ Technol Dept Chem Engn Tehran Polytech 424 Hafez Ave Tehran 158754413 Iran Amirkabir Univ Technol Dept Petr Engn Tehran Polytech 424 Hafez Ave Tehran 158754413 Iran

Rate of penetration (ROP) prediction is crucial for drilling optimization because of its role in minimizing drilling costs. There are many factors, which determine the drilling rate of penetration. Typical factors include formation properties, mud rheology, weight on bit, bit rotation speed, type of bit, wellbore inclination, and bit hydraulics. In this paper, first, the simultaneous effect of six variables on penetration rate using real field drilling data has been investigated. Response surface methodology (RSM) was used to develop a mathematical relation between penetration rate and six factors. The important variables include well depth (D), weight on bit (WOB), bit rotation speed (N), bit jet impact force (IF), yield point to plastic viscosity ratio (Y-p/PV), 10 min to 10 s gel strength ratio (10MGS/10SGS). Next, bat algorithm (BA) was used to identify optimal range of factors in order to maximize drilling rate of penetration. Results indicate that the derived statistical model provides an efficient tool for estimation of ROP and determining optimum drilling conditions. Sensitivity study using analysis of variance shows that well depth, yield point to plastic viscosity ratio, weight on bit, bit rotation speed, bit jet impact force, and 10 min to 10 s gel strength ratio have the greatest effect on ROP variation respectively. Cumulative probability distribution of predicted ROP shows that the penetration rate can be estimated accurately at 95% confidence interval. In addition, study shows that by increasing well depth, there is an uncertainty in selecting the jet impact force as the best objective function to determine the effect of hydraulics on penetration rate. (C) 2016 Elsevier B.V. All rights reserved.

关键词： Drilling Penetration rate Response surface methodology bat algorithm

来源：评论

学校读者我要写书评

暂无评论

ECO-bat: A New Routing Protocol for Energy Consumption Optimization Based on bat algorithm in WSN

引用

Computers, Materials & Continua 2021年第2期66卷 1497-1510页

作者： Mohammed Kaddi Abdallah Banana Mohammed Omari LDDI Laboratory Mathematics and Computer Science DepartmentUniversity of AdrarAdrar01000Algeria Mathematics and Computer Science Department University of AdrarAdrar01000Algeria

Wireless sensor network (WSN) has been widely used due to its vastrange of applications. The energy problem is one of the important problems influencingthe complete application. Sensor nodes use very small batteries as a powersource and replacing them is not an easy task. With this restriction, the sensornodes must conserve their energy and extend the network lifetime as long as ***, these limits motivate much of the research to suggest solutions in alllayers of the protocol stack to save energy. So, energy management efficiencybecomes a key requirement in WSN design. The efficiency of these networks ishighly dependent on routing protocols directly affecting the network *** is one of the most popular techniques preferred in routing *** this work we propose a novel energy-efficient protocol for WSN based on a batalgorithm called ECO-bat (Energy Consumption Optimization with bat algorithmfor WSN) to prolong the network lifetime. We use an objective function thatgenerates an optimal number of sensor clusters with cluster heads (CH) to minimizeenergy consumption. The performance of the proposed approach is comparedwith Low-Energy Adaptive Clustering Hierarchy (LEACH) and EnergyEfficient cluster formation in wireless sensor networks based on the Multi-Objective bat algorithm (EEMOB) protocols. The results obtained are interestingin terms of energy-saving and prolongation of the network lifetime.

关键词： WSNs network lifetime routing protocols ECO-bat bat algorithm CH energy consumption LEACH EEMOB

来源：评论

学校读者我要写书评

暂无评论

Path Generation for a Given Performance Evaluation Value Interval by Modifying bat algorithm with Heuristic

引用

INTERNATIONAL JOURNAL OF SOFTWARE ENGINEERING AND KNOWLEDGE ENGINEERING 2023年第5期33卷 787-814页

作者： Wang, Fujun Cao, Zining Li, Zhen Xing, Chao Zong, Hui Nanjing Univ Aeronaut & Astronaut Coll Comp Sci & Technol Nanjing 211106 Peoples R China Minist Ind & Informat Technol Key Lab Safety Crit Software Nanjing 211106 Peoples R China Nanjing Univ Aeronaut & Astronaut Collaborat Innovat Ctr Novel Software Technol & In Nanjing 211106 Peoples R China Sci & Technol Electroopt Control Lab Luoyang 471000 Peoples R China

Path generation means generating a path or a set of paths so that the generated path meets specified properties or constraints. To our knowledge, generating a path with the performance evaluation value of the path within a given value interval has received scant attention. This paper subtly formulates the path generation problem as an optimization problem by designing a reasonable fitness function, adapts the Markov decision process with reward model into a weighted digraph by eliminating multiple edges and non-goal dead nodes, constructs the path by using a priority-based indirect coding scheme, and finally modifies the bat algorithm with heuristic to solve the optimization problem. Simulation experiments were carried out for different objective functions, population size, number of nodes, and interval ranges. Experimental results demonstrate the effectiveness and superiority of the proposed algorithm.

关键词： Path generation performance evaluation heuristic algorithm bat algorithm

来源：评论

学校读者我要写书评

暂无评论

Improvements of bat algorithm for optimal feature selection: A systematic literature review

引用

INTELLIGENT DATA ANALYSIS 2022年第1期26卷 5-31页

作者： Al-Dyani, Wafa Zubair Ahmad, Farzana Kabir Kamaruddin, Siti Sakira Univ Utara Malaysia Coll Arts & Sci Sch Comp Sintok 06010 Malaysia Hadhramout Univ Coll Comp & Informat Technol Dept Comp Sci Hadhramout Yemen

bat algorithm (BA) has been extensively applied as an optimal Feature Selection (FS) technique for solving a wide variety of optimization problems due to its impressive characteristics compared to other swarm intelligence methods. Nevertheless, BA still suffers from several problems such as poor exploration search, falling into local optima, and has many parameters that need to be controlled appropriately. Consequently, many researchers have proposed different techniques to handle such problems. However, there is a lack of systematic review on BA which could shed light on its variants. In the literature, several review papers have been reported, however, such studies were neither systematic nor comprehensive enough. Most studies did not report specifically which components of BA was modified. The range of improvements made to the BA varies, which often difficult for any enhancement to be accomplished if not properly addressed. Given such limitations, this study aims to review and analyse the recent variants of latest improvements in BA for optimal feature selection. The study has employed a standard systematic literature review method on four scientific databases namely, IEEE Xplore, ACM, Springer, and Science Direct. As a result, 147 research publications over the last ten years have been collected, investigated, and summarized. Several critical and significant findings based on the literature reviewed were reported in this paper which can be used as a guideline for the scientists in the future to do further research.

关键词： bat algorithm feature selection bat improvements systematic review

来源：评论

学校读者我要写书评

暂无评论

A novel scanning bat algorithm strategy for maximum power point tracker of partially shaded photovoltaic energy systems

引用

AIN SHAMS ENGINEERING JOURNAL 2020年第4期11卷 1093-1103页

作者： Eltamaly, Ali M. Al-Saud, M. S. Abokhalil, Ahmed G. King Saud Univ Sustainable Energy Technol Ctr Riyadh 11421 Saudi Arabia Mansoura Univ Elect Engn Dept Mansoura Egypt King Saud Univ Coll Engn Elect Engn Dept Riyadh 11421 Saudi Arabia Majmaah Univ Elect Engn Dept Almajmaah 11952 Saudi Arabia Assiut Univ Elect Engn Dept Assiut 71515 Egypt

bat algorithm (BA) is used to track the global peak (GP) of photovoltaic (PV) energy systems due to its fast convergence. Meanwhile, BA has many limitations when it is used as maximum power point tracker (MPPT) of PV systems like the need for re-initialization, and the problem of premature convergence. These problems are solved in this paper by injecting one flying bat to search for greater power than the value of current global best to avoid reinitialization of bats. This proposed strategy sends the flying bat to positions of anticipated peaks when the generated power is changed with certain value to remove the need for reinitialization with highest confidence of capturing the GP. Moreover, the convergence time is reduced by at least 566% compared to the state of the art strategy. The results obtained from this novel strategy showed its superiority in tracking the GP under all operating conditions. (c) 2020 The Authors. Published by Elsevier B.V. on behalf of Faculty of Engineering, Ain Shams University. This is an open access article under the CC BY-NC-ND license (http://***/licenses/by-nc-nd/4.0/).

关键词： Photovoltaic MPPT Partial shading bat algorithm Initialization Scanning bat

来源：评论

学校读者我要写书评

暂无评论

Modified bat algorithm based on covariance adaptive evolution for global optimization problems

引用

SOFT COMPUTING 2018年第16期22卷 5215-5230页

作者： Shan, Xian Cheng, Huijin China Univ Petr Sch Sci Qingdao 266580 Peoples R China China Univ Petr Sch Econ & Management Qingdao 266580 Peoples R China

bat algorithm is a newly proposed swarm intelligence algorithm inspired by the echolocation behavior of bats, which has been successfully used in many optimization problems. However, due to its poor exploration ability, it still suffers from problems such as premature convergence and local optimum. In order to enhance the search ability of the algorithm, we propose an improved bat algorithm, which is based on the covariance adaptive evolution process. The information included in the covariance adaptive evolution diversifies the search directions and sampling distributions of the population, which is of great benefit to the search process. The proposed approaches have been tested on a set of benchmark functions. Experimental results indicate that the proposed algorithm obtains superior performance over the majority of the test problems.

关键词： bat algorithm Swarm intelligence Covariance adaptive evolution

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：