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Comparison of P-RnaPredict and mfold -: algorithms for RNA secondary structure prediction

BIOINFORMATICS 2006年第8期22卷 934-942页

作者： Wiese, KC Hendriks, A Simon Fraser Univ Sch Comp Sci Surrey BC V3T 5X3 Canada Simon Fraser Univ InfoNet Media Ctr Surrey BC V3T 5X3 Canada

Motivation: Ribonucleic acid is vital in numerous stages of protein synthesis;it also possesses important functional and structural roles within the cell. The function of an RNA molecule within a particular organic system is principally determined by its structure. The current physical methods available for structure determination are time-consuming and expensive. Hence, computational methods for structure prediction are sought after. The energies involved by the formation of secondary structure elements are significantly greater than those of tertiary elements. Therefore, RNA structure prediction focuses on secondary structure. Results: We present P-RnaPredict, a parallel evolutionary algorithm for RNA secondary structure prediction. The speedup provided by parallelization is investigated with five sequences, and a dramatic improvement in speedup is demonstrated, especially with longer sequences. An evaluation of the performance of P-RnaPredict in terms of prediction accuracy is made through comparison with 10 individual known structures from 3 RNA classes (5S rRNA, Group I intron 16S rRNA and 16S rRNA) and the mfold dynamic programming algorithm. P-RnaPredict is able to predict structures with higher true positive base pair counts and lower false positives than mfold on certain sequences.

关键词： parallel genetic algorithm THERMODYNAMIC PARAMETERS MISMATCHES ENERGETICS STABILITY HELICES

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Multi-niche crowding in the development of parallel genetic simulated annealing 05

Multi-niche crowding in the development of parallel genetic ...

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Proceedings of the 7th annual conference on genetic and evolutionary computation

作者： Zhi-Gang Wang M. Rahman Yoke-San Wong National University of Singapore Singapore

ISBN: (纸本)9781595930101

In this paper, a new hybrid of genetic algorithm (GA) and simulated annealing (SA), referred to as GSA, is presented. In this algorithm, SA is incorporated into GA to escape from the local optima. Then, the idea of hierarchical parallel GA is borrowed to parallelize GSA for the optimization of multimodal functions. In addition, multi-niche crowding is used to maintain the diversity in the population of parallel GSA. The performance of the proposed algorithms is evaluated against a standard set of multimodal benchmark functions. Multi-niche crowding PGSA and normal PGSA show some remarkable improvement in comparison with the conventional parallel GA and the breeder genetic algorithm.

关键词： parallel genetic algorithm genetic algorithm simulated annealing

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genetic algorithm for optimizing the nonlinear time alignment of automatic speech recognition systems

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IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS 1996年第5期43卷 559-566页

作者： Kwong, S Chau, CW Halang, WA City University of Hong Kong Hong Kong China Hagen Germany

Dynamic time warping (DTW) is a nonlinear time-alignment technique for automatic speech recognition (ASR) systems, It had been widely used in many commercial and industrial products, ranging from electronic dailies/dictionaries to wireless voice digit dialers, DTW has the advantages of fast training and searching times, which makes it more popular than other available ASR techniques, However, there exist some limitations to DTW, such as the stringent rule on slope weighting, the nontrivial computation of the K-best paths, and the significant increase in computational time when the endpoint constraint is relaxed or the variations of the length of pattern increased, In this paper, a stochastic method called the genetic algorithm (GA), which is used to solve the nonlinear time alignment problem, is presented, Experimental results show that the GA has a better performance than the DTW, In addition, two derivatives of GA: the hybrid GA and the parallel GA are also presented.

关键词： dynamic time warping automatic speech recognition stochastic method genetic algorithm hybrid genetic algorithm parallel genetic algorithm

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Development of novel hybrid pre-separation/extractive reactive distillation processes for the separation of methanol/methyl acetate/ethyl acetate

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SEPARATION AND PURIFICATION TECHNOLOGY 2024年 348卷

作者： Zhu, Jiaxing Hao, Lin Zhu, Zhenxing Wei, Hongyuan Southwest Univ Sch Chem & Chem Engn Chongqing Peoples R China Tianjin Univ Sch Chem Engn & Technol Tianjin Univ Chem Proc Safety Lab Joint Green Separat & Chem Proc Safety Lab Tianjin Peoples R China Sinopec Res Inst Petr Proc Beijing 100083 Peoples R China

The treatment of waste streams is an important research topic for the sustainable development of chemical process. Recently, reactive distillation-based (RD) processes with ethylene oxide hydrolysis have been developed to separate water-containing azeotropic mixtures. To separate Serafimov's class 2.0-2b mixtures containing methanol/methyl acetate, a methyl acetate transesterification reaction between propylene glycol monomethyl ether is introduced to convert methyl acetate to methanol and coproduce produce propylene glycol monomethyl ether acetate as advanced solvents. Three-column reactive-extractive distillation (TCRED) and extractivereactive distillation (TCERD), and double-column pre-separation-reactive distillation (DCPSRD) processes, are proposed. Then, we use a parallel genetic algorithm to optimize processes to maximize total net revenue. The case study is methanol/methyl acetate/ethyl acetate. Though TCRED is not suitable due to the occurrence of ethyl acetate transesterification reactions, to compare economic performances of three RD-based processes, TCRED is regarded as a pseudo process. The total net revenue of three RD-based processes is relatively larger than (similar to 20 % increase) that of the conventional extractive distillation process. Compared with TCRED process, TCERD and DCPSRD can achieve $582336 and $1045995 increase in TNR, 27.43 % and 49.99 % TAC reduction, respectively. In summary, proposed RD-based processes are promising to separate Serafimov's class 2.0-2b mixtures containing methanol/methyl acetate, especially TCRED and DCPSRD.

关键词： Reactive distillation Extractive distillation Methyl acetate transesterification reaction parallel genetic algorithm Waste stream

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Guaranteeing the probability of success using repeated runs of genetic algorithm

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IMAGE AND VISION COMPUTING 2001年第8期19卷 551-560页

作者： Yuen, SY Fong, CK Lam, HS City Univ Hong Kong Dept Elect Engn Hong Kong Hong Kong Peoples R China

Though genetic algorithm (GA) has found widespread application, there appears to be no guarantee of success or quantitative measure of the probability of success in a given application. This paper addresses this problem using the notion of repeatedly applying a GA. Several alternative interpretations of the algorithm are offered. The Q factor is introduced to characterize the efficacy of any GA. The repeated algorithm is applied to a six-degree object detection problem and experimental results are reported. A general methodology is given on the design of GA in a particular problem based on defining the maximum variation of a problem, using the training set to estimate the average probability of a single run to the desired level of statistical confidence, and using the testing set to verify the required performance. This paper paves the way for applying the GA to robust industrial applications for which the probability of convergence to the globally correct solution is required to be arbitrarily high. (C) 2001 Elsevier Science B.V. All rights reserved.

关键词： parallel genetic algorithm repeated run probability of success

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Automatic Path Planning for Dual-Crane Lifting in Complex Environments Using a Prioritized Multiobjective PGA

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IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS 2018年第3期14卷 829-845页

作者： Cai, Panpan Chandrasekaran, Indhumathi Zheng, Jianmin Cai, Yiyu Nanyang Technol Univ Sch Mech & Aerosp Engn Singapore 639798 Singapore Natl Univ Singapore Sch Comp Singapore 119077 Singapore Nanyang Technol Univ Sch Comp Engn Singapore 639798 Singapore Nanyang Technol Univ Inst Media Innovat Singapore 639798 Singapore

Cooperative dual-crane lifting is an important but challenging process involved in heavy and critical lifting tasks. This paper considers the path planning for the cooperative dual-crane lifting. It aims to automatically generate optimal dual-crane lifting paths under multiple constraints, i.e., collision avoidance, coordination between the two cranes, and balance of the lifting target. Previous works often used oversimplified models for the dual-crane lifting system, the lifting environment, and the motion of the lifting target. They were thus limited to simple lifting cases and might even lead to unsafe paths in some cases. We develop a novel path planner for dual-crane lifting that can quickly produce optimized paths in complex 3-D environments. The planner has fully considered the kinematic structure of the lifting system. Therefore, it is able to robustly handle the nonlinear movement of the suspended target during lifting. The effectiveness and efficiency of the planner are enabled by three novel aspects: 1) a comprehensive and computationally efficient mathematical modeling of the lifting system;2) a new multiobjective parallel genetic algorithm designed to solve the path planning problem;and 3) a new efficient approach to perform continuous collision detection for the dual-crane lifting target. The planner has been tested in complex industrial environments. The results show that the planner can generate dual-crane lifting paths that are easy for conductions and optimized in terms of costs for complex environments. Comparisons with two previous methods demonstrate the advantages of the planner, including safer paths, higher success rates, and the ability to handle general lifting cases.

关键词： Continuous collision detection (CCD) dual-crane lifting graphic processing unit (GPU) computing multiobjective optimization parallel genetic algorithm robotic path planning

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Jobshop lot streaming with routing flexibility, sequence-dependent setups, machine release dates and lag time

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2012年第8期50卷 2331-2352页

作者： Defersha, Fantahun M. Chen, Mingyuan Concordia Univ Dept Mech & Ind Engn Montreal PQ H3G 1M8 Canada Univ Guelph Sch Engn Guelph ON N1G 2W1 Canada

Lot streaming is a technique of splitting production lots into smaller sublots in a multi-stage manufacturing system so that operations of a given lot can overlap. This technique can reduce the manufacturing makespan and is an effective tool in time-based manufacturing. Research on lot streaming models and solution procedures for flexible jobshops has been limited. The flexible jobshop scheduling problem is an extension of the classical jobshop scheduling problem by allowing an operation to be assigned to one of a set of eligible machines during scheduling. In this paper we develop a lot streaming model for a flexible jobshop environment. The model considers several pragmatic issues such as sequence-dependent setup times, the attached or detached nature of the setups, the machine release date and the lag time. In order to solve the developed model efficiently, an island-model parallel genetic algorithm is proposed. Numerical examples are presented to demonstrate the features of the proposed model and compare the computational performance of the parallel genetic algorithm with the sequential algorithm. The results are very encouraging.

关键词： lot streaming flexible jobshop scheduling sequence dependent setup machine release date lag time parallel genetic algorithm

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Trade-offs among planned versus performed activity patterns

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TRANSPORTMETRICA B-TRANSPORT DYNAMICS 2017年第3期5卷 347-368页

作者： Allahviranloo, Mahdieh Recker, Will Timmermans, Harry J. P. CUNY City Coll Dept Civil Engn New York NY 10031 USA Univ Calif Irvine Inst Transportat Studies Dept Civil & Environm Engn Irvine CA USA Eindhoven Univ Technol Urban Planning Grp Eindhoven Netherlands

This paper focuses on the development of a methodology to identify the latent factors leading to changes in the planned itineraries of travellers that result in their actual activity patterns. Specifically, we propose a way to utilise patterns of activities established by individuals across multiple days to generate possible alternative actions by these individuals when faced with conditions that produce a discrepancy between performed and planned patterns on a particular day. The choice alternatives, which are unobserved, are inferred by rules applied to comprehensive multiday data collected in Belgium, consisting of information regarding planned activity itineraries, performed activity/travel diaries, and demographics of travellers. These data are utilised to analyse and explore the underlying reasons preventing individuals from performing their planned activities on a given day, and to identify the influential parameters that lead individuals to trade their planned patterns with those actually performed. Using multiday data, we generate all possible combinations of categories of activities - mandatory, maintenance, discretionary, and pickup/drop off activities - that can form patterns for individuals. Under the assumption that the performed patterns have the closest utility to the planned patterns, we estimate the latent factors that influence travellers' time use behaviour using a multinomial probit choice structure in which the covariance structure of the choice alternatives is specified in terms of the overlap in activities. We further identify the 'costs' associated with making changes in planned agenda (replacing, inserting, or deleting an activity). These penalty values are estimated using 'parallel genetic algorithm', where the fitness function is the likelihood function estimated under the multinomial choice model structure. The results show that individuals' mobility decisions related to mandatory activities are more robust than those associated with the

关键词： activity trade-off pattern robustness agenda reliability parallel genetic algorithm

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A heuristic approach for detecting RNA H-type pseudoknots

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BIOINFORMATICS 2005年第17期21卷 3501-3508页

作者： Huang, CH Lu, CL Chiu, HT Natl Chiao Tung Univ Dept Biol Sci & Technol Hsinchu 300 Taiwan

Motivation: RNA H-type pseudoknots are ubiquitous pseudoknots that are found in almost all classes of RNA and thought to play very important roles in a variety of biological processes. Detection of these RNA H-type pseudoknots can improve our understanding of RNA structures and their associated functions. However, the currently existing programs for detecting such RNA H-type pseudoknots are still time consuming and sometimes even ineffective. Therefore, efficient and effective tools for detecting the RNA H-type pseudoknots are needed. Results: In this paper, we have adopted a heuristic approach to develop a novel tool, called HPknotter, for efficiently and accurately detecting H-type pseudoknots in an RNA sequence. In addition, we have demonstrated the applicability and effectiveness of HPknotter by testing on some sequences with known H-type pseudoknots. Our approach can be easily extended and applied to other classes of more general pseudoknots.

关键词： parallel genetic algorithm MOSAIC-VIRUS RNA SECONDARY STRUCTURE COMPUTER-SIMULATION INCLUDING PSEUDOKNOTS STRUCTURE PREDICTION INFORMATION THERMODYNAMICS IMPLEMENTATION REPLICATION

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GUILLOTINEABLE BIN PACKING - A genetic APPROACH

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 1995年第3期84卷 645-661页

作者： KROGER, B UNIV OSNABRUCK DEPT MATH & COMP SCID-40049 OSNABRUCKGERMANY

For a constrained, two-dimensional Bin Packing Problem this paper introduces a sequential and a parallel genetic algorithm. A guillotine constraint is directly reflected by the encoding mechanism and thus is ensured at any stage of the algorithm. As an enlargement, the concept of meta-rectangles is proposed and incorporated into the algorithm. Each meta-rectangle temporarily fixes (rectangular) hyperplanes of existing solutions. By this the hierarchical structure of guillotineable packing schemes is exploited to reduce the problem's complexity without affecting the quality of the generated solutions. The presented algorithm is able to generate almost optimal packing schemes and even in its sequential version the algorithm empirically is proven to be superior to different approaches like random search or simulated annealing.

关键词： 2-DIMENSIONAL BIN PACKING parallel genetic algorithm SIMULATED ANNEALING

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