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On the evaluation of the Bunch search-based software modularization algorithm

SOFT COMPUTING 2008年第1期12卷 77-93页

作者： Mitchell, Brian S. Mancoridis, Spiros Drexel Univ Dept Comp Sci Software Engn Res Grp Philadelphia PA 19104 USA

The first part of this paper describes an automatic reverse engineering process to infer subsystem abstractions that are useful for a variety of software maintenance activities. This process is based on clustering the graph representing the modules and module-level dependencies found in the source code into abstract structures not in the source code called subsystems. The clustering process uses evolutionary algorithms to search through the enormous set of possible graph partitions, and is guided by a fitness function designed to measure the quality of individual graph partitions. The second part of this paper focuses on evaluating the results produced by our clustering technique. Our previous research has shown through both qualitative and quantitative studies that our clustering technique produces good results quickly and consistently. In this part of the paper we study the underlying structure of the search space of several open source systems. We also report on some interesting findings our analysis uncovered by comparing random graphs to graphs representing real software systems.

关键词： reverse engineering software clustering search algorithms

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Harmony search algorithm for infinite impulse response system identification

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COMPUTERS & ELECTRICAL ENGINEERING 2014年第4期40卷 1265-1285页

作者： Saha, S. K. Kar, R. Mandal, D. Ghoshal, S. P. NIT Durgapur Dept Elect & Commun Engg Durgapur India NIT Durgapur Dept Elect Engg Durgapur W Bengal India

In this paper, optimal sets of filter coefficients are searched by a meta-heuristic optimization technique called Harmony search (HS) algorithm for infinite impulse response (IIR) system identification problem. For different optimization problems, HS algorithm undergoes three basic rules;namely Random Selection (RS), Harmony Memory Consideration (HMC), and Pitch Adjustment (PA) rules, which are inspired from the process that the musicians use to improvise a perfect state of harmony with the consummate skill of blending notes in tune. With the help of the properly selected control parameters, a perfect balance is achieved in exploration and exploitation in searching phases. The detailed analysis of simulation results emphasizes the strength of HS algorithm to find the near-global optimal solution, quality of convergence profile and the speed of convergence while tested against standard benchmark examples for same and reduced order models. (c) 2014 Elsevier Ltd. All rights reserved.

关键词： search algorithms IMPULSE response SYSTEM identification METAHEURISTIC algorithms PROBLEM solving COMPUTER simulation

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An Improved Global Harmony search Algorithm for the Identification of Nonlinear Discrete-Time Systems Based on Volterra Filter Modeling

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MATHEMATICAL PROBLEMS IN ENGINEERING 2016年第1期2016卷 1-13页

作者： Li, Zongyan Li, Deliang China Univ Min & Technol Sch Informat & Elect Engn Xuzhou 221116 Jiangsu Peoples R China Xuzhou Coll Ind Technol Xuzhou 221140 Jiangsu Peoples R China

This paper describes an improved global harmony search (IGHS) algorithm for identifying the nonlinear discrete-time systems based on second-order Volterra model. The IGHS is an improved version of the novel global harmony search (NGHS) algorithm, and it makes two significant improvements on the NGHS. First, the genetic mutation operation is modified by combining normal distribution and Cauchy distribution, which enables the IGHS to fully explore and exploit the solution space. Second, an opposition-based learning (OBL) is introduced and modified to improve the quality of harmony vectors. The IGHS algorithm is implemented on two numerical examples, and they are nonlinear discrete-time rational system and the real heat exchanger, respectively. The results of the IGHS are compared with those of the other three methods, and it has been verified to be more effective than the other three methods on solving the above two problems with different input signals and system memory sizes.

关键词： search algorithms DISCRETE-time systems VOLTERRA equations CAUCHY problem SIGNAL processing

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Optimum Design of Gravity Retaining Walls Using Charged System search Algorithm

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MATHEMATICAL PROBLEMS IN ENGINEERING 2012年第1期2012卷 1-10页

作者： Talatahari, S. Sheikholeslami, R. Shadfaran, M. Pourbaba, M. Univ Tabriz Marand Fac Engn Tabriz Iran Amirkabir Univ Technol Dept Civil & Environm Engn Tehran Iran Univ Tabriz Dept Civil Engn Tabriz Iran Islamic Azad Univ Dept Civil Engn Maragheh Branch Maragheh Iran

This study focuses on the optimum design retaining walls, as one of the familiar types of the retaining walls which may be constructed of stone masonry, unreinforced concrete, or reinforced concrete. The material cost is one of the major factors in the construction of gravity retaining walls therefore, minimizing the weight or volume of these systems can reduce the cost. To obtain an optimal seismic design of such structures, this paper proposes a method based on a novel metaheuristic algorithm. The algorithm is inspired by the Coulomb's and Gauss's laws of electrostatics in physics, and it is called charged system search (CSS). In order to evaluate the efficiency of this algorithm, an example is utilized. Comparing the results of the retaining wall designs obtained by the other methods illustrates a good performance of the CSS. In this paper, we used the Mononobe-Okabe method which is one of the pseudostatic approaches to determine the dynamic earth pressure.

关键词： STRUCTURAL optimization RETAINING wall design & construction search algorithms CONCRETE COULOMB'S law DIVERGENCE theorem

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Quantum Behaved Particle Swarm Optimization with Neighborhood search for Numerical Optimization

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MATHEMATICAL PROBLEMS IN ENGINEERING 2013年第1期2013卷 1-10页

作者： Fu, Xiao Liu, Wangsheng Zhang, Bin Deng, Hua Air Force Aviat Univ Dept Fundamental Courses Changchun 130022 Peoples R China Air Force Aviat Univ Dept Aviat Survival Changchun 130022 Peoples R China

Quantum-behaved particle swarm optimization (QPSO) algorithm is a new PSO variant, which outperforms the original PSO in search ability but has fewer control parameters. However, QPSO as well as PSO still suffers from premature convergence in solving complex optimization problems. The main reason is that new particles in QPSO are generated around the weighted attractors of previous best particles and the global best particle. This may result in attracting too fast. To tackle this problem, this paper proposes a new QPSO algorithm called NQPSO, in which one local and one global neighborhood search strategies are utilized to balance exploitation and exploration. Moreover, a concept of opposition-based learning (OBL) is employed for population initialization. Experimental studies are conducted on a set of well-known benchmark functions including multimodal and rotated problems. Computational results show that our approach outperforms some similar QPSO algorithms and five other state-of-the-art PSO variants.

关键词： PARTICLE swarm optimization search algorithms NUMERICAL analysis QUANTUM computing STOCHASTIC convergence ATTRACTORS (Mathematics) MULTIMODAL user interfaces (Computer systems)

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Efficient search Methods for Statistical Dependency Rules

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FUNDAMENTA INFORMATICAE 2011年第2期113卷 117-150页

作者： Hamalainen, Wilhelmiina Univ Eastern Finland Dept Biosci Kuopio Finland

Dependency analysis is one of the central problems in bioinformatics and all empirical science. In genetics, for example, an important problem is to find which gene alleles are mutually dependent or which alleles and diseases are dependent. In ecology, a similar problem is to find dependencies between different species or groups of species. In both cases a classical solution is to consider all pairwise dependencies between single attributes and evaluate the relationships with some statistical measure like the chi(2)-measure. It is known that the actual dependency structures can involve more attributes, but the existing computational methods are too inefficient for such an exhaustive search. In this paper, we introduce efficient search methods for positive dependencies of the form X -> A with typical statistical measures. The efficiency is achieved by a special kind of a branch-and-bound search which also prunes out redundant rules. Redundant attributes are especially harmful in dependency analysis, because they can blur the actual dependencies and even lead to erroneous conclusions. We consider two alternative definitions of redundancy: the classical one and a stricter one. We improve our previous algorithm for searching for the best strictly non-redundant dependency rules and introduce a totally new algorithm for searching for the best classically non-redundant rules. According to our experiments, both algorithms can prune the search space very efficiently, and in practice no minimum frequency thresholds are needed. This is an important benefit, because biological data sets are typically dense, and the alternative search methods would require too large minimum frequency thresholds for any practical purpose.

关键词： statistical dependence redundancy chi(2)-measure z-score search algorithms

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Design of disassembly sequences using search strategies. Application of IDA* in state diagrams

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INTERNATIONAL JOURNAL OF PRODUCTION REsearch 2011年第11期49卷 3395-3403页

作者： Reyes Selva, Anibal Cespon Castro, Roberto Fuentes Frias, Victor G. Univ Holguin Dept Ind Engn Holguin Cuba Cent Univ Martha Abreu Las Villas Dept Ind Engn Santa Clara Cuba

The main aim of a disassembly process is to reuse components and reduce the negative impact it has on the environment. Reaching an efficient and effective sequence of disassembly has become one of the major concerns in this field. This article refers to the use of iterative deepening A* search (artificial intelligence), in the design of the disassembly sequence. This method is applied to the state diagrams, a simple representation of the different states in a disassembly sequence. This way, the design process gains efficiency by finding the final sequence in the first iteration;therefore removing the need to analyse all possible sequences, since the best possible sequence is known in the first iteration. The method can also be applied to mechanical, electromechanical and electronic appliances with the aim of obtaining components for reuse or final disposal. Experimental results demonstrate the applicability and effectiveness of the methodology.

关键词： search algorithms disassembly artificial intelligence

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Applicability of Cuckoo search Algorithm for the Prediction of Multicomponent Liquid-Liquid Equilibria for Imidazolium and Phosphonium Based Ionic Liquids

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INDUSTRIAL & ENGINEERING CHEMISTRY REsearch 2015年第49期54卷 12393-12407页

作者： Bharti, Anand Prerna Banerjee, Tamal Indian Inst Technol Guwahati Dept Chem Engn Gauhati 781039 Assam India Birla Inst Technol Dept Chem Engn Ranchi 835215 Jharkhand India

Cuckoo search (CS), which is a nature-inspired stochastic optimization method, has been successfully applied for estimating binary interaction parameters of universal quasichemical (UNIQUAC) and nonrandom two-liquid (NRTL) activity coefficient models for liquid liquid ternary systems involving 12 imidazolium and phosphonium ionic liquids (ILs). Thirty-nine ternary systems, comprising 371 experimental tie-lines, were correlated by the UNIQUAC and NRTL models. The results, expressed by deviations between experimental and calculated mole fractions, are very satisfactory, with global deviation values of 0.0053 (UNIQUAC) and 0.0072 (NRTL), which are 63% and 45% better than literature reported values. Three quaternary systems and one quinary system were taken from literature to compare the capability of CS algorithm with genetic algorithm (GA) and particle swarm optimization (PSO) algorithm. The global % root-mean-square deviation (RMSD) value obtained with CS algorithm was similar to 0.14-0.85% as compared to similar to 1.0-2.0% with GA and PSO algorithms. This shows a higher efficiency for the CS algorithm in solving global optimization problems involved in the thermodynamic modeling of multicomponent systems.

关键词： MULTIPHASE flow LIQUID-liquid equilibrium search algorithms PREDICTION models IMIDAZOLES PHOSPHONIUM compounds IONIC liquids

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Capacitor allocations in radial distribution networks using cuckoo search algorithm

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IET GENERATION TRANSMISSION & DISTRIBUTION 2014年第2期8卷 223-232页

作者： El-Fergany, Attia A. Abdelaziz, Almoataz Y. Zagazig Univ Fac Engn Dept Elect Power & Machines Zagazig Egypt Ain Shams Univ Fac Engn Dept Elect Power & Machines Cairo Egypt

In the present work, a cuckoo search optimisation-based approach has been developed to allocate static shunt capacitors along radial distribution networks. The objective function is adopted to minify the system operating cost at different loading conditions and to improve the system voltage profile. In addition to find the optimal location and values of the fixed and switched capacitors in distribution networks with different loading levels using the proposed algorithm. Higher potential buses for capacitor placement are initially identified using power loss index. However, that method has proven less than satisfactory as power loss indices may not always indicate the appropriate placement. At that moment, the proposed approach identifies optimal sizing and placement and takes the final decision for optimum location within the number of buses nominated with minimum number of effective locations and with lesser injected VArs. The overall accuracy and reliability of the approach have been validated and tested on radial distribution systems with differing topologies and of varying sizes and complexities. The results shown by the proposed approach have been found to outperform the results of existing heuristic algorithms found in the literature for the given problem. [ABSTRACT FROM AUTHOR]

关键词： CAPACITORS RADIAL distribution function ELECTRIC networks search algorithms LOAD (Electric power) ELECTRIC power distribution

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Variable Neighbourhood search and Mathematical Programming for Just-in-Time Job-Shop Scheduling Problem

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MATHEMATICAL PROBLEMS IN ENGINEERING 2014年第1期2014卷 1-9页

作者： Wang, Sunxin Li, Yan Xian Univ Technol Sch Higher Vocat & Tech Educ Xian 710082 Peoples R China Xian Univ Technol Sch Mech & Precis Instrument Engn Xian 710048 Peoples R China

This paper presents a combination of variable neighbourhood search and mathematical programming to minimize the sum of earliness and tardiness penalty costs of all operations for just-in-time job-shop scheduling problem (JITJSSP). Unlike classical E/T scheduling problem with each job having its earliness or tardiness penalty cost, each operation in this paper has its earliness and tardiness penalties, which are paid if the operation is completed before or after its due date. Our hybrid algorithm combines (i) a variable neighbourhood search procedure to explore the huge feasible solution spaces efficiently by alternating the swap and insertion neighbourhood structures and (ii) a mathematical programming model to optimize the completion times of the operations for a given solution in each iteration procedure. Additionally, a threshold accepting mechanism is proposed to diversify the local search of variable neighbourhood search. Computational results on the 72 benchmark instances show that our algorithm can obtain the best known solution for 40 problems, and the best known solutions for 33 problems are updated.

关键词： search algorithms VARIABLES (Mathematics) MATHEMATICAL programming JUST-in-time systems PRODUCTION scheduling PROBLEM solving

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