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A binary bat algorithm with improved crossover operators and Cauchy mutation for unit commitment problem

JOURNAL OF SUPERCOMPUTING 2024年第8期80卷 11261-11292页

作者： Pang, Aokang Liang, Huijun Lin, Chenhao Yao, Lei Hubei Minzu Univ Coll Intelligent Syst Sci & Engn 39 Xueyuan Rd Enshi 445000 Hubei Peoples R China Enshi Power Supply Co State Grid Hubei Elect Power Co 96 Hangkong Ave Enshi 445000 Hubei Peoples R China

Power system operators are faced with the problem of unit commitment belonging to mixed integer programming, which becomes very complicated, as units become large-scale and highly constrained. Because unit commitment problem is a binary problem with commitment and de-commitment, a discrete/binary optimization algorithm with superior performance is required. This paper proposes a novel hybrid binary bat algorithm for unit commitment problem, which consists of two process. To begin with, the proposed binary bat algorithm is applied to determining the commitment schedule of unit commitment problem. Specifically, an improved crossover operator based on exponential-logic-modulo map is proposed to enhance the convergence and maintain the diversity of populations. To prevent the algorithm from falling into a local optimum, a local mutation strategy performs local perturbation. Chaotic map is responsible for updating some parameters to increase the performance of the proposed algorithm. Furthermore, Lambda-iteration method is adopted to solve economic load dispatch in continuous space. Constraint handling is performed using the heuristic constraint produce. The effectiveness of the proposed algorithm is verified by benchmark functions and test systems. Additionally, the simulation results are compared with other well-established heuristic and binary approaches.

关键词： Bat algorithm binary algorithm Unit commitment problem Local mutation Crossover operator

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A novel binary fruit fly optimization algorithm for solving the multidimensional knapsack problem

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KNOWLEDGE-BASED SYSTEMS 2013年 48卷 17-23页

作者： Wang, Ling Zheng, Xiao-long Wang, Sheng-yao Tsinghua Univ Dept Automat Tsinghua Natl Lab Informat Sci & Technol TNList Beijing 100084 Peoples R China

In this paper, a novel binary fruit fly optimization algorithm (bFOA) is proposed to solve the multidimensional knapsack problem (MKP). In the bFOA, binary string is used to represent the solution of the MKP, and three main search processes are designed to perform evolutionary search, including smell-based search process, local vision-based search process and global vision-based search process. In particular, a group generating probability vector is designed for producing new solutions. To enhance the exploration ability, a global vision mechanism based on differential information among fruit flies is proposed to update the probability vector. Meanwhile, two repair operators are employed to guarantee the feasibility of solutions. The influence of the parameter setting is investigated based on the Taguchi method of design of experiment. Extensive numerical testing results based on benchmark instances are provided. And the comparisons to the existing algorithms demonstrate the effectiveness of the proposed bFOA in solving the MKP, especially for the large-scale problems. (c) 2013 Elsevier B.V. All rights reserved.

关键词： Multidimensional knapsack problem Fruit fly optimization algorithm binary algorithm Smell-based search Vision-based search

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binary Artificial Electric Field algorithm

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EVOLUTIONARY INTELLIGENCE 2023年第4期16卷 1155-1183页

作者： Chauhan, Dikshit Yadav, Anupam Dr BR Ambedkar Natl Inst Technol Jalandhar Dept Math Jalandhar 144011 Punjab India

Artificial Electric Field algorithm (AEFA) is one of the recent population-based optimization techniques, it is inspired by the electrostatic force theory. This article aims to design a novel binary version of the AEFA scheme to improve the performance of the original AEFA scheme in discrete space. The popular S-shaped and V-shaped functions are used to design the binary versions of the AEFA. The efficiency and the optimization ability of the proposed binary versions of the AEFA are studied theoretically as well as experimentally. An extensive experimental study is performed to understand the performance of the proposed schemes. A set of 24 benchmark problems are solved using binary versions of AEFA the experimental results are compared with nine state-of-the-art algorithms. The running time complexity and Wilcoxon's signed-rank statistical test are also conducted to judge the proposed algorithms. In addition to the experimental studies, theoretical analysis is also carried out which suggests the convergence scenario of the proposed schemes. These studies suggest that the designed binary versions of the AEFA are very efficient and competent in addressing difficult optimization problems.

关键词： Meta heuristic algorithms Optimization Artificial Electric Field algorithm Benchmark problems binary algorithm S-shaped function V-shaped function

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Research on A dynamic binary stack anti-collision algorithm

Research on A dynamic binary stack anti-collision algorithm

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2nd International Conference on Applied Mechanics, Materials and Manufacturing (ICAMMM 2012)

作者： Yi, Jianjun Luo, Fei Chen, Shaoli Ji, Baiyang Yan, Haixu East China Univ Sci & Technol Shanghai 200237 Peoples R China Sunyard Sys Engn Co Ltd Hangzhou 310053 Peoples R China

ISBN: (纸本)9783037855799

RFID anti-collision technology is one of a key technology in RFID application system. Anti-collision algorithms for RFID systems include tag anti-collision algorithms and reader anti-collision algorithms. This paper focused on the impoved binary algorithm and dynamic binary algorithm. An improved algorithm has been proposed, in which the collision bits was put into the stack and they were used as the reader's request. Based on this mechanism, a novel binary stack algorithm has been proposed. Its simulation was given to analyze the performance of this algorithm. The simulation results showed that the amount of transmitted data in proposed algorithm was obviously less than those in the other two traditional algorithms with the number of tags and their bytes increasing. Consequently, the performance of the proposed algorithm is much better than that of the traditional anti-collision binary algorithm.

关键词： RFID anti-collision algorithm binary algorithm dynamic binary algorithm stack

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A comprehensive analysis of grid-based wind turbine layout using an efficient binary invasive weed optimization algorithm with levy flight

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EXPERT SYSTEMS WITH APPLICATIONS 2022年 198卷 116835-116835页

作者： Koc, Ismail Konya Tech Univ Dept Software Engn Konya Turkey

Wind energy has attracted great attention in recent years due to the increasing demand for alternative energy sources. Gathering the maximum amount of energy from wind energy is directly related to the layout of wind turbines in wind farm. This study focuses on grid-based wind turbine layout problem in an area of 2 km x 2 km. In order to solve this problem, 9 novel grids of 11 x 11, 12 x 12, ... and 19 x 19 are proposed in this paper in addition to 10 x 10 and 20 x 20 turbine grids which have already used in the literature. A new repair operator is recommended, taking into account the distance constraint between two adjacent cells in turbine layout problem, and thus the obtained solutions are made feasible. Furthermore, a levy flight-based IWO (LFIWO) algorithm is developed to optimize the layout of the turbines in wind farm. The basic IWO algorithm and the proposed LFIWO algorithm are compared on 11 different turbine layouts. Experimental studies are carried out for both algorithms under equal conditions with the help of 10 different binary versions. According to the comparisons performed using 11 different grids, LFIWO demonstrates a much superior success than the IWO algorithm. In addition, the proposed 19 x 19 grid reveals the best success among the other grids. When compared to the other studies in the literature, it is seen that LFIWO surpasses the other algorithms in terms of solution quality. As a result, it can be clearly stated that the proposed binary version of LFIWO is a competitive and effective binary algorithm.

关键词： Invasive weed optimization Levy flight Wind turbine placement Turbine layout binary algorithm

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New Method for Generation of binary Pseudo-Random Sequences with Quasiperfect Autocorrelation 9

New Method for Generation of Binary Pseudo-Random Sequences ...

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9th International Kharkiv Symposium on Physics and Engineering of Microwaves, Millimeter and Submillimeter Waves (MSMW)

作者： Lukin, Konstantin Shcherbakov, Valery NAS Ukraine O Ya Usikov Inst Radiophys & Elect Lab Nonlinear Dynam Elect Syst Kharkov Ukraine

ISBN: (纸本)9781509022670

A new method for generation of unique binary pseudorandom sequences (BPR-sequences) has been suggested for applications in radars and communication systems. The method is based upon a modified discrete multi-dimensional chaotic map with two delays. The variants of generation of BPR-sequences by suggested algorithm has been investigated and analyzed using computer simulation. Correlation characteristics of BPR-sequences generated according to the suggested method have been studied and tested. It has been shown that the suggested algorithm generates the BPR-sequences having their correlation characteristics close enough to those of M-sequences. It has been shown that BPR-sequences, generated according to the method suggested, meet the requirements to the signals used in both radar and communication systems.

关键词： binary algorithm unique binary pseudorandom sequence modified discrete chaotic algorithm qusiperfect autocorrelation periodic autocorrelation function inverse periodic autocorrelation function

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Improvements of real coded genetic algorithms based on differential operators preventing premature convergence

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ADVANCES IN ENGINEERING SOFTWARE 2004年第3-4期35卷 237-246页

作者： Hrstka, O Kucerová, A Czech Tech Univ Prague Fac Civil Engn Dept Struct Mech Prague 16629 Czech Republic Czech Tech Univ Prague Fac Civil Engn Comp & Informat Ctr Prague 16629 Czech Republic

This paper presents several types of evolutionary algorithms used for global optimization on real domains. The interest has been focused, on multimodal problems, where the difficulties of a premature convergence usually occur. First the standard genetic algorithm using binary encoding of real values and its unsatisfactory behavior with multimodal problems is briefly reviewed together with some improvements of fighting premature convergence. Two types of real encoded methods based on differential operators are examined in detail: the differential evolution (DE), a very modem and effective method first published by Storn and Price [NAPFHIS, 1996], and the simplified real-coded differential genetic algorithm SADE proposed by the authors [Contributions to mechanics of materials and structures, 2000]. In addition, an improvement of the SADE method, called CERAF technology, enabling the population of solutions to escape from local extremes, is examined. All methods are tested on an identical set of objective functions and a systematic comparison based on a reliable methodology [Adv. Engng Software 32 (2000) 49] is presented. It is confirmed that real coded methods generally exhibit better behavior on real, domains than the binary algorithms, even when extended by several improvements. Furthermore, the positive influence of the differential operators due to their possibility of self-adaptation is demonstrated. From the reliability point of view, it seems that the real encoded differential algorithm, improved by the technology described in this paper, is a universal-and reliable method capable of solving all proposed test problems. (C) 2003 Published by Elsevier Ltd.

关键词： genetic algorithm binary algorithm reliability

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How important is a transfer function in discrete heuristic algorithms

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NEURAL COMPUTING & APPLICATIONS 2015年第3期26卷 625-640页

作者： Saremi, Shahrzad Mirjalili, Seyedali Lewis, Andrew Griffith Univ Sch Informat & Commun Technol Brisbane Qld 4111 Australia

Transfer functions are considered the simplest and cheapest operators in designing discrete heuristic algorithms. The main advantage of such operators is the maintenance of the structure and other continuous operators of a continuous algorithm. However, a transfer function may show different behaviour in various heuristic algorithms. This paper investigates the behaviour and importance of transfer functions in improving performance of heuristic algorithms. As case studies, two algorithms with different mechanisms of optimisation were chosen: Gravitational Search algorithm and Particle Swarm Optimisation. Eight transfer functions were integrated in these two algorithms and compared on a set of test functions. The results show that transfer functions may show diverse behaviours and have different impacts on the performance of algorithms, which should be considered when designing a discrete algorithm. The results also demonstrate the significant role of the transfer function in terms of improved exploration and exploitation of a heuristic algorithm.

关键词： binary optimisation Discrete optimisation Transfer function Evolutionary algorithm Heuristic algorithm binary algorithm Discrete algorithm

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An effective hybrid harmony search-based algorithm for solving multidimensional knapsack problems

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APPLIED SOFT COMPUTING 2015年 29卷 288-297页

作者： Zhang, Biao Pan, Quan-Ke Zhang, Xin-Li Duan, Pei-Yong Liaocheng Univ Coll Comp Sci Liaocheng 252059 Peoples R China Huazhong Univ Sci & Technol State Key Lab Digital Mfg Equipment & Technol Wuhan 430074 Peoples R China Liaocheng Univ Coll Math Sci Liaocheng 252059 Peoples R China

This study presents an effective hybrid algorithm based on harmony search (HHS) for solving multidimensional knapsack problems (MKPs). In the proposed HHS algorithm, a novel harmony improvisation mechanism is developed with the modified memory consideration rule and the global-best pitch adjustment scheme to enhance the global exploration. A parallel updating strategy is employed to enrich the harmony memory diversity. To well balance the exploration and the exploitation, the fruit fly optimization (FFO) scheme is integrated as a local search strategy. For solving MKPs, binary strings are used to represent solutions and two repair operators are applied to guarantee the feasibility of the solutions. The HHS is calibrated based on the Taguchi method of design-of-experiment. Extensive numerical investigations based on well-known benchmark instances are conducted. The comparative evaluations indicate the HHS is much more effective than the existing HS and FFO variants in solving MKPs. (C) 2015 Elsevier B.V. All rights reserved.

关键词： Multidimensional knapsack problem Harmony search Fruit fly optimization Evolutionary algorithms binary algorithm Meta-heuristic

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Automatic algorithm of Effectiveness of Accounting Management Systems based on Finite Element Simulation

Automatic Algorithm of Effectiveness of Accounting Managemen...

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International Conference on Mechatronics and Industrial Informatics (ICMII 2013)

作者： Cheng YaNing Beihua Univ Sch Econ Management Jilin Peoples R China

ISBN: (纸本)9783037856949

The right panel drawing direction is an important prerequisite for generating qualified parts, an important step before the panel forming simulation is to determine the reasonable direction of the drawing. Manually adjust parts in order to overcome rely on experience, the drawbacks to the drawing direction, the direction of the drawing punch and forming the contact area of the sheet as the goal of automatic determination algorithm. Objective function of the direction of the drawing for the variable contact area in the drawing direction of the feasible region, the use of heritage algorithms to optimize the objective function of the contact area and, ultimately feasible within the contact area corresponding to the drawing direction, that is the best drawing direction. The measured results show that the direction of the drawing based on genetic algorithm, the automatic algorithm can fast and accurate to obtain the optimal direction of drawing.

关键词： Automatic algorithm Automotive Covering Stamping Direction binary algorithm

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