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Handling constraints in combinatorial interaction testing in the presence of multi objective particle swarm and multithreading

Bestoun S. Ahmed, Luca M. Gambardella, Wasif Afzal, Kamal Z. Zamli
2017 Information and Software Technology  
To overcome the multi-judgment criteria for an optimal solution, the multi-objective particle swarm optimization and multithreading are used.  ...  Objective: This paper presents a new strategy, to construct combinatorial interaction test suites in the presence of constraints. Method: The design and algorithms are provided in detail.  ...  To overcome the multi-judgement criteria for an optimal solution, the multi-objective particle swarm optimisation and multithreading are used.  ... 
doi:10.1016/j.infsof.2017.02.004 fatcat:xv6dm2psxvhcbpubd3bb5qvqzq

Computational Air Traffic Management

Marc Anthony Azzopardi, James F. Whidborne
2011 2011 IEEE/AIAA 30th Digital Avionics Systems Conference  
A specific embodiment of a CATM system was designed, constructed, simulated and tested and shown to be a significant step towards demonstrating the feasibility of a fully autonomous multi-agent-based air  ...  The system offers unique advantages in terms of resilience to disruption, efficiency and future scalability.  ...  Both qualitative and quantitative tests were conducted in order to show symmetric distributed particle swarm optimisation in difficult cases, large scale traffic handling, dynamic optimisation and the  ... 
doi:10.1109/dasc.2011.6095967 fatcat:5kfu6ba5h5g7pdffh7z3ftdjai

A Comprehensive Survey on Particle Swarm Optimization Algorithm and Its Applications

Yudong Zhang, Shuihua Wang, Genlin Ji
2015 Mathematical Problems in Engineering  
Particle swarm optimization (PSO) is a heuristic global optimization method, proposed originally by Kennedy and Eberhart in 1995. It is now one of the most commonly used optimization techniques.  ...  On the other hand, we offered a survey on applications of PSO to the following eight fields: electrical and electronic engineering, automation control systems, communication theory, operations research  ...  Fuzzy logic was incorporated in the PSO algorithm to handle the multiobjective nature of the problem. Unified "And-Or" operator was used to aggregate the objectives.  ... 
doi:10.1155/2015/931256 fatcat:ubc5eywnhzdjllxjaywe4czhnm

Parallel bi-objective evolutionary algorithms for scalable feature subset selection via migration strategy under Spark [article]

Yelleti Vivek, Vadlamani Ravi, P. Radha Krishna
2022 arXiv   pre-print
In order to accomplish this, we parallelized the non-dominated sorting based algorithms namely non dominated sorting algorithm (NSGA-II), and non-dominated sorting particle swarm optimization (NSPSO),  ...  We test the effectiveness of the proposed methodology on various datasets.  ...  Multi objective evolutionary algorithms (MOEAs) are proven to be very effective in solving various combinatorial and continuous MOPs.  ... 
arXiv:2205.09465v1 fatcat:qvdqfzyikjhxdgyfhy6tvsmfsi

Parallel computational optimization in operations research: A new integrative framework, literature review and research directions

Guido Schryen
2019 European Journal of Operational Research  
of what has been achieved and still needs to be done in parallel optimization in OR.  ...  However, in the past decade substantial advancements in parallel computing capabilities have been achieved and used by OR scholars so that an overview of modern parallel optimization in OR that accounts  ...  Parallel evolutionary algorithm for single and multi-objective optimisation: differential evolution and constraints handling. Applied Soft Computing 61, 995-1012.  ... 
doi:10.1016/j.ejor.2019.11.033 fatcat:5olyajxlyrca7kmqscpgjef4vq

Software testing: a research travelogue (2000–2014)

Alessandro Orso, Gregg Rothermel
2014 Proceedings of the on Future of Software Engineering - FOSE 2014  
Our goal, in this paper, is to provide an accounting of some of the most successful research performed in software testing since the year 2000, and to present what appear to be some of the most significant  ...  relevant and noteworthy research performed in the area of software testing in the time period considered-a task that would require far more space and time than we have available.  ...  We are extremely grateful to all of our colleagues who found time to respond (in several cases quite extensively) to our request for input on contributions and challenges in the area of software testing  ... 
doi:10.1145/2593882.2593885 dblp:conf/icse/OrsoR14 fatcat:qrgtbowbubaexljt7fmhr3euzm

Optimization of hybrid parallel application execution in heterogeneous high performance computing systems considering execution time and power consumption [article]

Paweł Rościszewski
2018 arXiv   pre-print
methodology for such execution aiming for minimization of the contradicting objectives of application execution time and power consumption of the utilized computing hardware.  ...  Both meanings of the application hybridity result in multiplicity of execution parameters of nontrivial interdependences and influence on the considered optimization criteria.  ...  For example, multi-objective optimization using Particle Swarm Optimization (PSO) algorithm with energy-aware cost function and task deadlines has been proposed in [105] for partitioning tasks on heterogeneous  ... 
arXiv:1809.07611v1 fatcat:f2vl3kmgznckroj6h3uwt2zwf4

A Review on Community Detection in Large Complex Networks from Conventional to Deep Learning Methods: A Call for the Use of Parallel Meta-Heuristic Algorithms

Mohammed Al-Andoli, Shing Chiang Tan, Wooi Ping Cheah, Sin Yin Tan
2021 IEEE Access  
[122] also adapted multi-objective BA optimization to address the CD problem. The concept of Pareto dominance is used to select the optimal solution in multi-objective optimization.  ...  Many particles are randomly created over the search space to form a swarm. Each particle is generated in such a way that it represents a solution candidate for the optimization problem.  ... 
doi:10.1109/access.2021.3095335 fatcat:4zggvxofqvbcjbwylk7swc3c34

An Evolutionary Game-Based Mechanism for Routing P2P Network Flow among Selfish Peers

Fang Zuo, Wei Zhang
2014 Journal of Networks  
Networking devices are increasing in complexity among various services and platforms, from different vendors. The network complexity is required experts' operators.  ...  The DAIM model uses a group of standard switches, databases, and corresponding between them by using DAIM agents.  ...  is also affected by the constraints of the similarity between the particles, thus ensuring particle swarm certain diversity and avoid premature convergence.  ... 
doi:10.4304/jnw.9.01.10-17 fatcat:tbmafdamk5am7a6ba26gsxzydq

Framework for Computation Offloading in Mobile Cloud Computing

Dejan Kovachev, Ralf Klamma
2012 International Journal of Interactive Multimedia and Artificial Intelligence  
ACKNOWLEDGEMENTS This proposal was carried out in the network of advanced technology research in Francisco José de Caldas University in Bogotá Colombia, as part of the Ph.D. in Engineering, within the  ...  ACKNOWLEDGMENT This work is supported by the Excellence Initiative of German National Science Foundation (DFG) within the research cluster Ultra High-Speed Mobile Information and Communication (UMIC) and  ...  It also performs better than fuzzy BSO (Fuzzy Bat Swarm Optimization) [10] in all test cases.  ... 
doi:10.9781/ijimai.2012.171 fatcat:zeqxsym4f5ashmjkiivje2uoau

A Novel Approach for the Process Planning and Scheduling Problem Using the Concept of Maximum Weighted Independent Set [article]

Kai Sun
2020 arXiv   pre-print
In this paper, we propose a novel approach to formulate a general type of the PPS problem with resource allocation and process planning integrated towards a typical objective, minimizing the makespan.  ...  The different weight configurations of the proposed approach for solving the PPS problem are tested on a real-world PPS example and further designated test instances to evaluate the scalability, accuracy  ...  2003), agent-based approach (Shen et al., 2006; Wong et al., 2006), particle swarm optimization algorithm (Guo et al., 2006) and genetic algorithm (Zhang et al., 1997; Morad & Zalzala, 1999; Jia et al.  ... 
arXiv:2008.01960v3 fatcat:3vhkwdgkrzewrjpy5pjiqbq6zy

Toward virtual biopsy through an all fiber optic ultrasonic miniaturized transducer: a proposal

A. Acquafresca, E. Biagi, L. Masotti, D. Menichelli
2003 IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control  
Created by The Institute of Electrical and Electronics Engineers (IEEE) for the benefit of humanity.  ...  Created by The Institute of Electrical and Electronics Engineers (IEEE) for the benefit of humanity.  ... 
doi:10.1109/tuffc.2003.1244749 fatcat:l3jre4etsvcqzfyz2jqggji3gy

Video Bioinformatics Methods for Analyzing Cell Dynamics: A Survey [chapter]

Nirmalya Ghosh
2015 Computational Biology  
This book chapter reviews state of the art in all these stages and directs further research with references from the above-established fields, including key thrust areas like quantitative cell tracking  ...  segmentation to cellular feature extraction and selection, classification into different phenotypes, and exploration of hidden content-based patterns in bioimaging databases.  ...  All the biological events in the list require some kind of particle tracking and then classification of the dynamics.  ... 
doi:10.1007/978-3-319-23724-4_2 fatcat:wjsaagwnpbgmziy662tsmw6hv4

PyBioNetFit and the Biological Property Specification Language

Eshan D. Mitra, Ryan Suderman, Joshua Colvin, Alexander Ionkov, Andrew Hu, Herbert M. Sauro, Richard G. Posner, William S. Hlavacek
2019 iScience  
We demonstrate the model checking and design applications of PyBioNetFit and BPSL by analyzing a model of targeted drug interventions in autophagy signaling.  ...  We demonstrate PyBioNetFit's capabilities by solving various example problems, including the challenging problem of parameterizing a 153-parameter model of cell cycle control in yeast based on both quantitative  ...  Computational resources used in this study included the following: the Darwin cluster at LANL, which is supported by the Computational Systems and Software Environment (CSSE) subprogram of the Advanced  ... 
doi:10.1016/j.isci.2019.08.045 pmid:31522114 pmcid:PMC6744527 fatcat:3ter3qo7mbgx5heluxxmfkaywe

In Silico Engineering of Proteins That Recognize Small Molecules [chapter]

Sushil Kumar, Gabriel Demo, Jaroslav Koca, Michaela Wimmerova
2012 Protein Engineering  
SO exploits the population of individual to probe the premising region of search space. The population is called swarm and the individuals are called particles.  ...  Particle Swarm optimization (PSO) is one of the evolutionary computational techniques inspired by the social behaviour.  ...  A broad series of articles covering significant aspects of methods and applications in the design of novel proteins with different functions are presented.  ... 
doi:10.5772/28001 fatcat:xfxrgir2lngm7bw76ydydt73ha
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