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mine blast algorithm: A new population based algorithm for solving constrained engineering optimization problems

APPLIED SOFT COMPUTING 2013年第5期13卷 2592-2612页

作者： Sadollah, Ali Bahreininejad, Ardeshir Eskandar, Hadi Hamdi, Mohd Univ Malaya Fac Engn Kuala Lumpur 50603 Malaysia Semnan Univ Fac Engn Semnan Iran

A novel population-based algorithm based on the mine bomb explosion concept, called the mine blast algorithm (MBA), is applied to the constrained optimization and engineering design problems. A comprehensive comparative study has been carried out to show the performance of the MBA over other recognized optimizers in terms of computational effort (measured as the number of function evaluations) and function value (accuracy). Sixteen constrained benchmark and engineering design problems have been solved and the obtained results were compared with other well-known optimizers. The obtained results demonstrate that, the proposed MBA requires less number of function evaluations and in most cases gives better results compared to other considered algorithms. (C) 2012 Elsevier B. V. All rights reserved.

关键词： mine blast algorithm Metaheuristic Constrained optimization Engineering design problems Constraint handling Global optimization

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mine blast algorithm for environmental economic load dispatch with valve loading effect

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NEURAL COMPUTING & APPLICATIONS 2018年第1期30卷 261-270页

作者： Ali, E. S. Abd Elazim, S. M. Zagazig Univ Elect Power & Machine Dept Fac Engn Zagazig Egypt

Economic load dispatch (ELD) is the process of allocating the required load between the available generation units such that the cost of operation is minimized. The ELD problem is formulated as a nonlinear constrained optimization problem with both equality and inequality constraints. The dual-objective combined economic emission dispatch (CEED) problem is considering the environmental impacts that accumulated from emission of gaseous pollutants of fossil-fueled power plants. In this paper, an implementation of mine blast algorithm (MBA) to solve ELD and CEED problems in power systems is discussed. Results obtained by the proposed MBA are compared with other optimization algorithms for various power systems. The results introduced in this paper show that the proposed MBA outlasts other techniques in terms of total cost and computational time.

关键词： mine blast algorithm Economic load dispatch Combined economic emission dispatch Emission constraints Valve point loading effect

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mine blast algorithm for optimization of truss structures with discrete variables

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COMPUTERS & STRUCTURES 2012年第Jul.期102卷 49-63页

作者： Sadollah, Ali Bahreininejad, Ardeshir Eskandar, Hadi Hamdi, Mohd Univ Malaya Fac Engn Kuala Lumpur 50603 Malaysia Semnan Univ Dept Mech Engn Semnan Iran

In this study a novel optimization method is presented, the so called mine blast algorithm (MBA). The fundamental concepts and ideas of MBA are derived from the explosion of mine bombs in real world. The efficiency of the proposed optimizer is tested via the optimization of several truss structures with discrete variables and its performance is compared with several well-known metaheuristic algorithms. The results show that MBA is able to provide faster convergence rate and also manages to achieve better optimal solutions compared to other efficient optimizers. (C) 2012 Elsevier Ltd. All rights reserved.

关键词： Optimization mine blast algorithm Truss structures Discrete variables Metaheuristic

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Optimal design of fuzzy PID controller for deregulated LFC of multi-area power system via mine blast algorithm

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NEURAL COMPUTING & APPLICATIONS 2020年第9期32卷 4531-4551页

作者： Fathy, Ahmed Kassem, Ahmed M. Abdelaziz, Almoataz Y. Jouf Univ Elect Engn Dept Fac Engn Al Jouf Saudi Arabia Zagazig Univ Elect Power & Machines Dept Fac Engn Zagazig Egypt Sohag Univ Elect Engn Dept Fac Engn Sohag Egypt Ain Shams Univ Fac Engn Elect Power & Machines Dept Cairo Egypt

This paper presents a novel optimal fuzzy proportional-integral-derivative (fuzzy PID) controller for load frequency control (LFC) designed by a proposed approach of mine blast algorithm (MBA) for multi-interconnected areas. The system includes reheat thermal connected power systems with the effect of the governor dead zone and turbine generation rate constraint nonlinearity. The proposed approach is used to determine the optimal parameters of the fuzzy PID controller to minimize the integral time absolute error. The proposed controller is inserted in multi-interconnected power systems which are built in Simulink/MATLAB library;triangular membership function is used for fuzzy PID controller. Additionally, the optimum adjustment of the fuzzy PID controller parameters under contracted scenario for large step demands and disturbances is investigated by MBA. The obtained results are compared to those obtained via antlion optimizer, artificial bee colony, hybrid differential evolution particle swarm optimization and hybrid PSO pattern search algorithm. The obtained results confirmed the superiority of the proposed MBA in designing the fuzzy PID-LFC as it provides less error with best statistical parameters compared to the others.

关键词： Load frequency control Fuzzy logic control mine blast algorithm

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Optimal locations and sizing of capacitors in radial distribution systems using mine blast algorithm

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ELECTRICAL ENGINEERING 2018年第1期100卷 1-9页

作者： Abd Elazim, S. M. Ali, E. S. Zagazig Univ Elect Power & Machine Dept Fac Engn Zagazig Egypt

In this paper, a mine blast algorithm (MBA) is proposed for optimal allocations and sizing of capacitors in various distribution systems. First, the most candidate buses for installing capacitors are suggested using loss sensitivity factors (LSF). Then, the proposed MBA is employed to deduce the size of capacitors and their locations from the elected buses. The objective function is designed to reduce the total cost and, consequently, to increase the net saving per year. The proposed algorithm is tested on 10 and 85 bus radial distribution systems. The obtained results via the proposed algorithm are compared with others to highlight their benefits. Moreover, the results are introduced to verify the effectiveness of the suggested algorithm to minimize the losses and total cost and to enhance the voltage profile and net saving for various distribution systems and loading conditions.

关键词： mine blast algorithm Power systems Optimal capacitor locations Loss sensitivity factors Distribution systems

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A hybrid mine blast algorithm for feature selection problems

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SOFT COMPUTING 2021年第1期25卷 517-534页

作者： Alweshah, Mohammed Alkhalaileh, Saleh Albashish, Dheeb Mafarja, Majdi Bsoul, Qusay Dorgham, Osama Al Balqa Appl Univ Dept Comp Sci Salt Jordan Birzeit Univ Dept Comp Sci Birzeit Palestine German Jordanian Univ Dept Comp Sci Amman Jordan

Feature selection (FS) is the process of finding the least possible number of features that are able to describe a dataset in the same way as the original features. Feature selection is a crucial preprocessing step for data mining techniques as it improves the performance of the prediction process in terms of speed and accuracy and also provides a better understanding of stored data. The success of the FS process depends on achieving a balance between two important factors, namely selecting the minimal number of features and maintaining the maximum accuracy in the results. In this paper, two methods are proposed to improve the FS process. Firstly, the mine blast algorithm (MBA) is introduced to optimize the FS process in the exploration phase. Secondly, the MBA is hybridized with simulated annealing as a local search in the exploitation phase to enhance the solutions located by the MBA. The proposed approaches (MBA and MBA-SA) are tested on 18 benchmark datasets from the UCI repository, and the comprehensive experimental results indicate that MBA-SA achieved good performance when compared with five approaches in the literature.

关键词： Feature selection Simulated annealing mine blast algorithm Hybrid optimization Classification

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Improved mine blast algorithm for optimal cost design of water distribution systems

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ENGINEERING OPTIMIZATION 2015年第12期47卷 1602-1618页

作者： Sadollah, Ali Yoo, Do Guen Kim, Joong Hoon Korea Univ Sch Civil Environm & Architectural Engn Seoul South Korea

The design of water distribution systems is a large class of combinatorial, nonlinear optimization problems with complex constraints such as conservation of mass and energy equations. Since feasible solutions are often extremely complex, traditional optimization techniques are insufficient. Recently, metaheuristic algorithms have been applied to this class of problems because they are highly efficient. In this article, a recently developed optimizer called the mine blast algorithm (MBA) is considered. The MBA is improved and coupled with the hydraulic simulator EPANET to find the optimal cost design for water distribution systems. The performance of the improved mine blast algorithm (IMBA) is demonstrated using the well-known Hanoi, New York tunnels and Balerma benchmark networks. Optimization results obtained using IMBA are compared to those using MBA and other optimizers in terms of their minimum construction costs and convergence rates. For the complex Balerma network, IMBA offers the cheapest network design compared to other optimization algorithms.

关键词： water distribution systems mine blast algorithm metaheuristics constrained optimization

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Geometry optimization of a cylindrical fin heat sink using mine blast algorithm

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INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2014年第5-8期73卷 795-804页

作者： Sadollah, Ali Eskandar, Hadi Kim, Joong Hoon Korea Univ Sch Civil Environm & Architectural Engn Seoul 136713 South Korea Semnan Univ Fac Engn Dept Mech Engn Semnan Iran

The heat sinks are utilized in electronic devices to eliminate heat from the chip and efficiently transmit it to the environment. Therefore, the optimal geometry sizes of fin heat sinks are the point of concern for manufacturers and designers. For this reason, the importance of optimization techniques particularly metaheuristics is understood. The design variables are width of heat sink, number of fins, fin height, and fin diameter. The various responses that have been considered are electromagnetic emitted radiations, thermal resistance, and mass of the heat sink investigated separately and simultaneously (multi-objective). mine blast algorithm (MBA), as a recently developed optimizer, is inspired from explosion of mines. The optimum dimensions and values for each response have been obtained by the MBA and have been compared with other optimization methods in the literature. In terms of thermal resistance and mass responses, the MBA has offered better values, while for the emitted radiations, the obtained results obtained by Taguchi-based gray relational analysis (TGRA) was preferred. For manufacturing point of view, the MBA and TGRA both suggested better and efficient design. In addition, the value path analysis has been carried out to compare the trade-off among the considered responses. Finally, parametric sensitivity analyses have been implemented for design parameters, and discussions and comparisons have been carried out for the effects of each decision variable. By considering all responses, width of heat sink and fin height are considered as the most important and effective design parameters, respectively.

关键词： Heat sink Multi-objective optimization mine blast algorithm Metaheuristic algorithms Design optimization

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An Efficient Hybrid mine blast algorithm for Tackling Software Fault Prediction Problem

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NEURAL PROCESSING LETTERS 2023年第8期55卷 10925-10950页

作者： Alweshah, Mohammed Kassaymeh, Sofian Alkhalaileh, Saleh Almseidin, Mohammad Altarawni, Ibrahim Al Balqa Appl Univ Prince Abdullah bin Ghazi Fac Commun & Informat Te Dept CS Salt Jordan Aqaba Univ Technol Fac Informat Technol Artificial Intelligence Dept Aqaba Jordan Aqaba Univ Technol Fac Informat Technol Software Engn Dept Aqaba Jordan Univ Kebangsaan Malaysia Fac Informat Sci & Technol CAIT Bangi Malaysia Tafila Tech Univ Comp Sci Dept Tafila Jordan

An inherent problem in software engineering is that competing prediction systems have been found to produce conflicting results. Yet accurate prediction is crucial because the complexity and quality of software requirements have dramatically changed in recent years, and consumers have become considerably more demanding in terms of the cost, timeframe, and quality of software solutions. Moreover, these variables may also be in direct conflict and can only be resolved by the optimum development of software by using reliable software engineering strategies. In this paper, a novel method based on the integration of the mine blast algorithm (MBA) and the simulated annealing (SA) algorithm is used to create input connection weights and biases for a back propagation neural network (BPNN) for the purpose of addressing the software fault prediction problem (SFP). The aim of hybridizing the MBA and SA is to find a way to efficiently explore and manipulate the search space. The proposed MBA-SA was tested on 18 datasets for SFP. The results indicated that the MBA-SA outperformed the MBA on all datasets. These results were subjected to additional statistical validity, boxplot distribution, and convergence analysis. Furthermore, a comparative evaluation of MBA-SA against twenty state-of-the-art methods for various output metrics was performed, and the result indicated that the hybrid MBA-SA outperformed most other state-of-the-art methods in the majority of datasets.

关键词： Software engineering prediction problems Machine learning Backpropagation neural network mine blast algorithm Simulated annealing Hybridization metaheuristic

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The mine blast algorithm for the structural optimization of electrical vehicle components

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MATERIALS TESTING 2020年第5期62卷 497-501页

作者： Yildiz, Betul Sultan Uludag Univ Dept Automot Engn Bursa Turkey

The shape optimization of mechanical and automotive component plays a crucial role in the development of auto-motive technology. Presently, the use of derivative-free metaheuristics in combination with finite element analysis for mechanical component design is one of the most focused on topics due to its simplicity and effectiveness. In this research paper, the mine blast algorithm (MBA) is used to solve the problem of shape optimization for a vehicle door hinge to prove how the MBA can be used for solving shape optimization problems in designing electrical vehicles. The results show the advantage of the MBA for designing optimal components in the automotive industry.

关键词： mine blast algorithm control arm shape optimization finite element analysis

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