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Artificial bee colony optimization for economic dispatch with valve point effect

Yacine LABBI,Djilani Ben ATTOUS,Belkacem MAHDAD

《能源前沿（英文）》 2014年 第8卷 第4期   页码 449-458 doi: 10.1007/s11708-014-0316-8

摘要： In recent years, various heuristic optimization methods have been proposed to solve economic dispatch (ED) problem in power systems. This paper presents the well-known power system ED problem solution considering valve-point effect by a new optimization algorithm called artificial bee colony (ABC). The proposed approach has been applied to various test systems with incremental fuel cost function, taking into account the valve-point effects. The results show that the proposed approach is efficient and robust when compared with other optimization algorithms reported in literature.

关键词： artificial bee colony (ABC) algorithm     economic dispatch (ED)     valve-point effect     optimization    

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Hybrid optimization algorithm for modeling and management of micro grid connected system

Kallol ROY,Kamal Krishna MANDAL

《能源前沿（英文）》 2014年 第8卷 第3期   页码 305-314 doi: 10.1007/s11708-014-0308-8

摘要： In this paper, a hybrid optimization algorithm is proposed for modeling and managing the micro grid (MG) system. The management of distributed energy sources with MG is a multi-objective problem which consists of wind turbine (WT), photovoltaic (PV) array, fuel cell (FC), micro turbine (MT) and diesel generator (DG). Because, perfect economic model of energy source of the MG units are needed to describe the operating cost of the output power generated, the objective of the hybrid model is to minimize the fuel cost of the MG sources such as FC, MT and DG. The problem formulation takes into consideration the optimal configuration of the MG at a minimum fuel cost, operation and maintenance costs as well as emissions reduction. Here, the hybrid algorithm is obtained as artificial bee colony (ABC) algorithm, which is used in two stages. The first stage of the ABC gets the optimal MG configuration at a minimum fuel cost for the required load demand. From the minimized fuel cost functions, the operation and maintenance cost as well as the emission is reduced using the second stage of the ABC. The proposed method is implemented in the Matlab/Simulink platform and its effectiveness is analyzed by comparing with existing techniques. The comparison demonstrates the superiority of the proposed approach and confirms its potential to solve the problem.

关键词： micro grid (MG)     multi-objective function     artificial bee colony (ABC)     fuel cost     operation and maintenance cost    

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An improved artificial bee colony algorithm with MaxTF heuristic rule for two-sided assembly line balancing

Xiaokun DUAN, Bo WU, Youmin HU, Jie LIU, Jing XIONG

《机械工程前沿（英文）》 2019年 第14卷 第2期   页码 241-253 doi: 10.1007/s11465-018-0518-6

摘要： Two-sided assembly line is usually used for the assembly of large products such as cars, buses, and trucks. With the development of technical progress, the assembly line needs to be reconfigured and the cycle time of the line should be optimized to satisfy the new assembly process. Two-sided assembly line balancing with the objective of minimizing the cycle time is called TALBP-2. This paper proposes an improved artificial bee colony (IABC) algorithm with the MaxTF heuristic rule. In the heuristic initialization process, the MaxTF rule defines a new task’s priority weight. On the basis of priority weight, the assignment of tasks is reasonable and the quality of an initial solution is high. In the IABC algorithm, two neighborhood strategies are embedded to balance the exploitation and exploration abilities of the algorithm. The employed bees and onlooker bees produce neighboring solutions in different promising regions to accelerate the convergence rate. Furthermore, a well-designed random strategy of scout bees is developed to escape local optima. The experimental results demonstrate that the proposed MaxTF rule performs better than other heuristic rules, as it can find the best solution for all the 10 test cases. A comparison of the IABC algorithm and other algorithms proves the effectiveness of the proposed IABC algorithm. The results also denote that the IABC algorithm is efficient and stable in minimizing the cycle time for the TALBP-2, and it can find 20 new best solutions among 25 large-sized problem cases.

关键词： two-sided assembly line balancing problem     artificial bee colony algorithm     heuristic rules     time boundary    

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改进二进制人工蜂群算法求解多维背包问题

王志刚,夏慧明

《中国工程科学》 2014年 第16卷 第8期   页码 106-112

摘要：

针对二进制人工蜂群算法收敛速度慢、易陷入局部最优的缺点，提出一种改进的二进制人工蜂群算法。新算法对人工蜂群算法中的邻域搜索公式进行了重新设计，并通过Bayes 公式来决定食物源的取值概率。将改进后的算法应用于求解多维背包问题，在求解过程中利用贪婪算法对进化过程中的不可行解进行修复，对背包资源利用不足的可行解进行修正。通过对典型多维背包问题的仿真实验，表明了本文算法在解决多维背包问题上的可行性和有效性。

关键词： 人工蜂群算法     多维背包问题     贪婪算法     组合优化    

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Novel hybrid models of ANFIS and metaheuristic optimizations (SCE and ABC) for prediction of compressive

Dung Quang VU; Fazal E. JALAL; Mudassir IQBAL; Dam Duc NGUYEN; Duong Kien TRONG; Indra PRAKASH; Binh Thai PHAM

《结构与土木工程前沿（英文）》 2022年 第16卷 第8期   页码 1003-1016 doi: 10.1007/s11709-022-0846-9

摘要： In this study, we developed novel hybrid models namely Adaptive Neuro Fuzzy Inference System (ANFIS) optimized by Shuffled Complex Evolution (SCE) on the one hand and ANFIS with Artificial Bee Colony (ABC) on the other hand. These were used to predict compressive strength (Cs) of concrete relating to thirteen concrete-strength affecting parameters which are easy to determine in the laboratory. Field and laboratory tests data of 108 structural elements of 18 concrete bridges of the Ha Long-Van Don Expressway, Vietnam were considered. The dataset was randomly divided into a 70:30 ratio, for training (70%) and testing (30%) of the hybrid models. Performance of the developed fuzzy metaheuristic models was evaluated using standard statistical metrics: Correlation Coefficient (R), Root Mean Square Error (RMSE) and Mean Absolute Error (MAE). The results showed that both of the novel models depict close agreement between experimental and predicted results. However, the ANFIS-ABC model reflected better convergence of the results and better performance compared to that of ANFIS-SCE in the prediction of the concrete Cs. Thus, the ANFIS-ABC model can be used for the quick and accurate estimation of compressive strength of concrete based on easily determined parameters for the design of civil engineering structures including bridges.

关键词： shuffled complex evolution     artificial bee colony     ANFIS     concrete     compressive strength     Vietnam    

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Damage assessment and diagnosis of hydraulic concrete structures using optimization-based machine learning technology

《结构与土木工程前沿（英文）》   页码 1281-1294 doi: 10.1007/s11709-023-0975-9

摘要： Concrete is widely used in various large construction projects owing to its high durability, compressive strength, and plasticity. However, the tensile strength of concrete is low, and concrete cracks easily. Changes in the concrete structure will result in changes in parameters such as the frequency mode and curvature mode, which allows one to effectively locate and evaluate structural damages. In this study, the characteristics of the curvature modes in concrete structures are analyzed and a method to obtain the curvature modes based on the strain and displacement modes is proposed. Subsequently, various indices for the damage diagnosis of concrete structures based on the curvature mode are introduced. A damage assessment method for concrete structures is established using an artificial bee colony backpropagation neural network algorithm. The proposed damage assessment method for dam concrete structures comprises various modal parameters, such as curvature and frequency. The feasibility and accuracy of the model are evaluated based on a case study of a concrete gravity dam. The results show that the damage assessment model can accurately evaluate the damage degree of concrete structures with a maximum error of less than 2%, which is within the required accuracy range of damage identification and assessment for most concrete structures.

关键词： hydraulic structure     curvature mode     damage detection     artifical neural network     artificial bee colony    

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改进的二进制人工蜂群算法 Research Articles

Rafet DURGUT

《信息与电子工程前沿（英文）》 2021年 第22卷 第8期   页码 1080-1091 doi: 10.1631/FITEE.2000239

摘要： 人工蜂群算法是一种基于群体智能并受蜜蜂觅食行为启发的演变优化算法。由于人工蜂群算法已被开发用于搜索连续的搜索空间来获得最优解，因此需要对其进行修改以应用于二进制优化问题。本文修改了人工蜂群算法来解决二进制优化问题，并将其命名为改进的二进制人工蜂群算法。提出的方法包括基于适应值和不同决策变量选择的更新机制。因此，我们的目标是通过增加探索能力来防止人工蜂群算法陷入局部最小值。将改进的二进制人工蜂群算法与人工蜂群算法的3种变体和其他文献中的启发式算法进行了比较，并使用了大家熟知的OR-Library数据集，其中包含为无容量限制的设施选址位置问题准备的15个问题实例。计算结果表明，该算法在收敛速度和鲁棒性方面均优于其他算法。可通过https://github.com/rafetdurgut/ibinABC获取算法源码。

关键词： 人工蜂群；二进制优化；无容量限制的设施选址位置问题（UFLP）    

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energy at hydrothermal power plants by simultaneous minimization of pollution and costs using improved ABC

Homayoun EBRAHIMIAN,Bahman TAHERI,Nasser YOUSEFI

《能源前沿（英文）》 2015年 第9卷 第4期   页码 426-432 doi: 10.1007/s11708-015-0376-4

摘要： The aim of this paper is simultaneous minimization of hydrothermal units to reach the best solution by employing an improved artificial bee colony (ABC) algorithm in a multi-objective function consisting of economic dispatch (ED) considering the valve-point effect and pollution function in power systems in view of the hot water of the hydro system. In this type of optimization problem, all practical constraints of units were taken into account as much as possible in order to comply with the reality. These constraints include the maximum and minimum output power of units, the constraints caused by the balance between supply and demand, the impact of pollution, water balance, uneven production curve considering the valve-point effect and system losses. The proposed algorithm is applied on the studied system, and the obtained results indifferent operating conditions are analyzed. To investigate in various operating conditions, different load profiles in 12 h are taken into account. The obtained results are compared with those of the other methods including the genetic algorithm (GA), the Basu technique, and the improved genetic algorithm. Fast convergence is one of this improved algorithm features.

关键词： practical constraints of units     pollution function     inlet steam valve     up-ramp rate of units     improved ABC algorithm    

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Ant colony optimization for assembly sequence planning based on parameters optimization

Zunpu HAN, Yong WANG, De TIAN

《机械工程前沿（英文）》 2021年 第16卷 第2期   页码 393-409 doi: 10.1007/s11465-020-0613-3

摘要： As an important part of product design and manufacturing, assembly sequence planning (ASP) has a considerable impact on product quality and manufacturing costs. ASP is a typical NP-complete problem that requires effective methods to find the optimal or near-optimal assembly sequence. First, multiple assembly constraints and rules are incorporated into an assembly model. The assembly constraints and rules guarantee to obtain a reasonable assembly sequence. Second, an algorithm called SOS-ACO that combines symbiotic organisms search (SOS) and ant colony optimization (ACO) is proposed to calculate the optimal or near-optimal assembly sequence. Several of the ACO parameter values are given, and the remaining ones are adaptively optimized by SOS. Thus, the complexity of ACO parameter assignment is greatly reduced. Compared with the ACO algorithm, the hybrid SOS-ACO algorithm finds optimal or near-optimal assembly sequences in fewer iterations. SOS-ACO is also robust in identifying the best assembly sequence in nearly every experiment. Lastly, the performance of SOS-ACO when the given ACO parameters are changed is analyzed through experiments. Experimental results reveal that SOS-ACO has good adaptive capability to various values of given parameters and can achieve competitive solutions.

关键词： assembly sequence planning     ant colony optimization     symbiotic organisms search     parameter optimization    

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Multi-objective optimal design of braced frames using hybrid genetic and ant colony optimization

Mehdi BABAEI,Ebrahim SANAEI

《结构与土木工程前沿（英文）》 2016年 第10卷 第4期   页码 472-480 doi: 10.1007/s11709-016-0368-4

摘要： In this article, multi-objective optimization of braced frames is investigated using a novel hybrid algorithm. Initially, the applied evolutionary algorithms, ant colony optimization (ACO) and genetic algorithm (GA) are reviewed, followed by developing the hybrid method. A dynamic hybridization of GA and ACO is proposed as a novel hybrid method which does not appear in the literature for optimal design of steel braced frames. Not only the cross section of the beams, columns and braces are considered to be the design variables, but also the topologies of the braces are taken into account as additional design variables. The hybrid algorithm explores the whole design space for optimum solutions. Weight and maximum displacement of the structure are employed as the objective functions for multi-objective optimal design. Subsequently, using the weighted sum method (WSM), the two objective problem are converted to a single objective optimization problem and the proposed hybrid genetic ant colony algorithm (HGAC) is developed for optimal design. Assuming different combination for weight coefficients, a trade-off between the two objectives are obtained in the numerical example section. To make the final decision easier for designers, related constraint is applied to obtain practical topologies. The achieved results show the capability of HGAC to find optimal topologies and sections for the elements.

关键词： multi-objective     hybrid algorithm     ant colony     genetic algorithm     displacement     weighted sum method     steel braced frames    

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consideration of uncertainties for deployment of distributed energy resources using interactive honey bee

Iraj AHMADIAN,Oveis ABEDINIA,Noradin GHADIMI

《能源前沿（英文）》 2014年 第8卷 第4期   页码 412-425 doi: 10.1007/s11708-014-0315-9

摘要： This paper presents a novel modified interactive honey bee mating optimization (IHBMO) base fuzzy stochastic long-term approach for determining optimum location and size of distributed energy resources (DERs). The Monte Carlo simulation method is used to model the uncertainties associated with long-term load forecasting. A proper combination of several objectives is considered in the objective function. Reduction of loss and power purchased from the electricity market, loss reduction in peak load level and reduction in voltage deviation are considered simultaneously as the objective functions. First, these objectives are fuzzified and designed to be comparable with each other. Then, they are introduced into an IHBMO algorithm in order to obtain the solution which maximizes the value of integrated objective function. The output power of DERs is scheduled for each load level. An enhanced economic model is also proposed to justify investment on DER. An IEEE 30-bus radial distribution test system is used to illustrate the effectiveness of the proposed method.

关键词： component     distributed energy resources     fuzzy optimization     loss reduction     interactive honey bee mating optimization (IHBMO)     voltage deviation reduction     stochastic programming    

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蚁群算法的研究现状及其展望

段海滨,王道波,于秀芬

《中国工程科学》 2007年 第9卷 第2期   页码 98-102

摘要：

蚁群算法是近几年优化领域中新出现的一种启发式仿生类并行智能进化系统，该算法采用分布式并 行计算和正反馈机制，易于与其他方法结合，目前已经在众多组合优化领域中得到广泛应用。在介绍基本蚁群 算法数学模型的基础上，列举了进入２１世纪以来部分具有代表性的蚁群算法改进模型及其应用情况，然后重点 从算法的模型改进、理论分析、并行实现、应用领域、硬件实现、智能融合等角度对蚁群算法在今后的研究方 向作了系统分析与展望。

关键词： 蚁群算法     信息素     正反馈     优化    

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Ant colony optimization in continuous problem

YU Ling, LIU Kang, LI Kaishi

《机械工程前沿（英文）》 2007年 第2卷 第4期   页码 459-462 doi: 10.1007/s11465-007-0079-6

摘要： Based on the analysis of the basic ant colony optimization and optimum problem in a continuous space, an ant colony optimization (ACO) for continuous problem is constructed and discussed. The algorithm is efficient and beneficial to the study of the ant colony optimization in a continuous space.

关键词： beneficial     algorithm     efficient     continuous     ACO    

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采用嵌入时空距离的混合蚁群算法求解一类受限车辆路径问题 Research Article

冯振辉1,2,肖人彬1,3

《信息与电子工程前沿（英文）》 2023年 第24卷 第7期   页码 1062-1079 doi: 10.1631/FITEE.2200585

摘要： 本文研究了共享出行背景下一类受限车辆路径问题，该问题以用户订单为核心，每个订单具有预约时间限制以及起始点、目的地两个位置点转换，是典型的具有时间、空间双重约束的扩展车辆路径问题。根据该问题特征，我们建立了以运营成本最低和用户体验度最高为目标的路径规划模型。为更精确地求解模型，根据用户的时间和空间属性定义了时空距离表示函数，进而提出一种嵌入时空距离的混合蚁群算法。该算法可分为两个阶段，首先通过时空聚类，以用户之间时空距离为主要衡量指标对用户进行分类，为问题求解提供启发式信息；其次结合劳动分工策略和时空距离函数，提出一种改进蚁群算法进行优化求解，以得到最终调度路线。基于现有数据集和实际城市环境的仿真案例进行数值实验。与其他启发式算法相比，该算法将基准实例中求得的最短路径长度降低2%–14%；与其他现存路径规划算法相比，该算法在测试实例上求得的综合成本更有竞争力。最后，利用两个实际的城市环境仿真案例进一步验证了所提算法的有效性。

关键词： 受限车辆路径问题；时空距离函数；劳动分工策略；蚁群算法    

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基于渐进式蚁群优化的多处理器任务分配 Article

Hamid Reza BOVEIRI

《信息与电子工程前沿（英文）》 2017年 第18卷 第4期   页码 498-510 doi: 10.1631/FITEE.1500394

摘要： 任务调度优化是多处理器环境（如并行和分布式系统）取得良好性能所面临的最重要挑战之一。目前大多数任务调度算法基于列表调度法，该方法的基本思路是，以列表的形式准备一系列待调度的节点，赋予这些节点不同优先级，然后不断去除列表中优先级最高的节点，并将其分配给具有最早开始时间（Earliest start time, EST）的处理器。由此可见，该算法的完成时间主要由两大因素决定：（1）任务分配顺序的选择（次序子问题）；（2）选定顺序的任务如何分配给处理器（分配子问题）。已有文献提出了许多解决次序子问题的好办法，但分配子问题少有人涉及。本文研究结果显示：传统的按照最早开始时间分配任务的方法并非最优；基于蚁群优化算法，得到一种新的方法，可以获得高效得多的调度方案。

关键词： 蚁群优化；列表调度；多处理器任务图调度；并行与分布式系统    

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标题 作者 时间 类型 操作

Artificial bee colony optimization for economic dispatch with valve point effect

Yacine LABBI,Djilani Ben ATTOUS,Belkacem MAHDAD

期刊论文

Hybrid optimization algorithm for modeling and management of micro grid connected system

Kallol ROY,Kamal Krishna MANDAL

期刊论文

An improved artificial bee colony algorithm with MaxTF heuristic rule for two-sided assembly line balancing

Xiaokun DUAN, Bo WU, Youmin HU, Jie LIU, Jing XIONG

期刊论文

改进二进制人工蜂群算法求解多维背包问题

王志刚,夏慧明

期刊论文

Novel hybrid models of ANFIS and metaheuristic optimizations (SCE and ABC) for prediction of compressive

Dung Quang VU; Fazal E. JALAL; Mudassir IQBAL; Dam Duc NGUYEN; Duong Kien TRONG; Indra PRAKASH; Binh Thai PHAM

期刊论文

Damage assessment and diagnosis of hydraulic concrete structures using optimization-based machine learning technology

期刊论文

改进的二进制人工蜂群算法

Rafet DURGUT

期刊论文

energy at hydrothermal power plants by simultaneous minimization of pollution and costs using improved ABC

Homayoun EBRAHIMIAN,Bahman TAHERI,Nasser YOUSEFI

期刊论文

Ant colony optimization for assembly sequence planning based on parameters optimization

Zunpu HAN, Yong WANG, De TIAN

期刊论文

Multi-objective optimal design of braced frames using hybrid genetic and ant colony optimization

Mehdi BABAEI,Ebrahim SANAEI

期刊论文

consideration of uncertainties for deployment of distributed energy resources using interactive honey bee

Iraj AHMADIAN,Oveis ABEDINIA,Noradin GHADIMI

期刊论文

蚁群算法的研究现状及其展望

段海滨,王道波,于秀芬

期刊论文

Ant colony optimization in continuous problem

YU Ling, LIU Kang, LI Kaishi

期刊论文

采用嵌入时空距离的混合蚁群算法求解一类受限车辆路径问题

冯振辉1,2,肖人彬1,3

期刊论文

基于渐进式蚁群优化的多处理器任务分配

Hamid Reza BOVEIRI

期刊论文