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Optimisation-based verification process of obstacle avoidance systems for unicycle-like mobile robots

Sivaranjini Srikanthakumar, Wen-Hua Chen
2011 International Journal of Automation and Computing  
Local and global optimisation methods are used to search simultaneously for the worst case condition (minimum distance to the obstacle) and the worst case uncertain parameter combination for the two wheeled  ...  The GLOBAL optimisation with UNIRANDI local search method is applied to find the global solution for unicycle obstacle avoidance system.  ...  His research interests include the development of advanced control strategies and their applications in aerospace engineering. E-mail:  ... 
doi:10.1007/s11633-011-0590-4 fatcat:keal4s2isnecrbsmes6wa6bfdq

Page 119 of Journal of Research and Practice in Information Technology Vol. 28, Issue 4 [page]

1996 Journal of Research and Practice in Information Technology  
A number of optimisation methods have been applied to the microcluster problem.  ...  es § 4 2/RECT SEARCH METHOD APPLIED TO A MOLECULAR STRUCTURE PROBLEM es Numbe rof 10000000 + Distinct Minima 1000000 | 100000 + 10000 + 1000 + Numbe rof Atoms Figure 11: Distinct local minima for Lennard-Jones  ... 

Unbiased geometry optimisation of Morse atomic clusters

Wayne Pullan
2010 IEEE Congress on Evolutionary Computation  
This paper presents the results obtained using an unbiased Population Based Search (PBS) for optimising Morse atomic clusters.  ...  In addition, PBS is able to operate in a parallel mode for optimising larger clusters.  ...  Given that the Directed Optimisation operator is only applied to a cluster that has already been locally optimised using two-phase local search, it is clearly very effective in following the energy funnel  ... 
doi:10.1109/cec.2010.5586213 dblp:conf/cec/Pullan10 fatcat:rumwjjoynrhwhkau4ju5w4eqve

A Largest Empty Hypersphere Metaheuristic for Robust Optimisation with Implementation Uncertainty [article]

Martin Hughes, Marc Goerigk, Michael Wright
2018 arXiv   pre-print
The aim is to find a solution that optimises the worst possible performance over all possible perturbances. Previously, only few generic search methods have been developed for this setting.  ...  We consider box-constrained robust optimisation problems with implementation uncertainty. In this setting, the solution that a decision maker wants to implement may become perturbed.  ...  Table 6 : Average number of points evaluated in the 50 sample runs. For all test problems of dimension 7 or higher the full budget of 10,000 function evaluations was used in all sample runs.  ... 
arXiv:1809.02437v1 fatcat:duffpeia7nfnhn6dfq4pin4som

Combinatorial optimisation algorithms for a CAD workstation

W.L. Price, F.W. Woodhams
1990 Discrete Applied Mathematics  
Sequential versions of combinatorial optimisation algorithms which are based on random search heuristics are generally too slow to be of value to the interactive user of a CAD workstation.  ...  A significant gain in speed can be achieved by using concurrent algorithms to drive an optimising accelerator attached to the workstation.  ...  Then CC0 can be applied to the sub- Conclusions A class of combinatorial optimisation problems has been defined.  ... 
doi:10.1016/0166-218x(90)90102-i fatcat:g67xji3tenblnfszv4auknomam

Modelling constant weight codes using tabu search

J.A. Bland, D.J. Baylis
1997 Applied Mathematical Modelling  
A feature of tabu search is the use of a memory facility that inhibits entrapment of the search by local optima, enabling the algorithm to continue searching for global optima.  ...  In this paper a recently developed combinatorial optimisation technique known as tabu search is used to investigate lower bounds on the optimal sizes of some constant weight codes.  ...  As previously stated, for specified values of n and w, the problem is to determine the largest code with a specified minimum distance d.  ... 
doi:10.1016/s0307-904x(97)00019-x fatcat:7cd7hzsr5vgqvgmc4iwuu22tmy

Designing and characterising fitness landscapes with various operators

Marius Gheorghita, Irene Moser, Aldeida Aleti
2013 2013 IEEE Congress on Evolutionary Computation  
We show that the metric is able to identify the degree of difficulty that we expect the landscapes to pose for the employed local search operators.  ...  of the initial solutions is appropriate to optimise.  ...  Others, such as Ant Colony Optimisation [14] explicitly choose one or more results of a global search phase to apply a hill-climbing local search such as steepest ascent to.  ... 
doi:10.1109/cec.2013.6557904 dblp:conf/cec/GheorghitaMA13 fatcat:acda7v42mbg2zfi2dg5ziklzty

Visualising Evolution History in Multi- and Many-Objective Optimisation [article]

Mathew Walter, David Walker, Matthew Craven
2020 arXiv   pre-print
Evolutionary algorithms are widely used to solve optimisation problems.  ...  However, challenges of transparency arise in both visualising the processes of an optimiser operating through a problem and understanding the problem features produced from many-objective problems, where  ...  At each generation, the Euclidean distance between each pairwise individual in the population is calculated, and the minimum distance is saved from which the median minimum pairwise distance is calculated  ... 
arXiv:2006.12309v1 fatcat:rrf7tac6ofbkxd4tgcrcuolz6i

Guided local search joins the elite in discrete optimisation [chapter]

Christos Voudouris, Edward Tsang
2001 Constraint Programming and Large Scale Discrete Optimization  
GLS and FLS together have been applied to a non-trivial number of satisfiability and optimisation problems and achieved remarkable result.  ...  GLS sits on top of other local-search algorithms. The basic principle of GLS is to penalise features exhibited by the candidate solution when a localsearch algorithm settles in a local optimum.  ...  Acknowledgements The authors would like to thank Chang Wang, Jim Doran, Andrew Davenport, Kangmin Zhu, James Borrett, John Ford, Patrick Mills, Terry Warwick, Alvin Kwan, Richard Williams, T L Lau and  ... 
doi:10.1090/dimacs/057/03 dblp:conf/dimacs/VoudourisT98 fatcat:ndryiied6jbiffxwjzgp4b7hlq

Success rate group search optimiser

Mohammad Hasanzadeh, Sana Sadeghi, Alireza Rezvanian, Mohammad Reza Meybodi
2014 Journal of experimental and theoretical artificial intelligence (Print)  
The group search optimiser (GSO) algorithm is a newly found evolutionary algorithm that is inspired by animal-searching behaviour and group living theory.  ...  In this paper, we develop a modified GSO algorithm by using the success rate model to adjust the maximum pursuit distance parameter of the algorithm.  ...  Acknowledgements The authors would like to thank the anonymous reviewers for their valuable comments and suggestions which improved the paper. Notes 1.  ... 
doi:10.1080/0952813x.2014.971467 fatcat:2b24guonvnhetcrmabckhln5de

A Parallel Multi-objective Local Search for AEDB Protocol Tuning

Santiago Iturriaga, Patricia Ruiz, Sergio Nesmachnow, Bernabe Dorronsoro, Pascal Bouvry
2013 2013 IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum  
In this work, we propose a novel parallel multi-objective local search that optimises an energy efficient broadcasting algorithm in terms of coverage, energy used, broadcasting time, and network resources  ...  Therefore, multi-objective optimisation is needed for fine tuning the protocol.  ...  In order to apply the operator to the solution s, another solution t is randomly selected from the local population and used as reference to quantify the perturbation applied during the local search (lines  ... 
doi:10.1109/ipdpsw.2013.237 dblp:conf/ipps/IturriagaRNDB13 fatcat:iutp5qwhvjcadgzt7pikyrarei


Vitaly E. Podobedov
2007 Technological and Economic Development of Economy  
Properties of the regions of attraction are presented. Regularity of the attraction regions is required to be a special characteristic of the local optimisation algorithms.  ...  Deterministic chaos situations produced by local optimisation algorithms are considered.  ...  Then the local optimisation algorithm is applied many times to the function f.  ... 
doi:10.3846/13928619.2007.9637777 fatcat:icbi7n46qbf3zbhomi35ikqn2y

Simulated quantum computation of global minima

Jing Zhu, Zhen Huang, Sabre Kais
2009 Molecular Physics  
We demonstrate that a modified Grover's quantum algorithm can be applied to real problems of finding a global minimum using modest numbers of quantum bits.  ...  Finding the optimal solution to a complex optimization problem is of great importance in practically all fields of science, technology, technical design and econometrics.  ...  Acknowledgements We thank Jonathan Baugh for useful discussions and the Army Research Office (ARO) for funding.  ... 
doi:10.1080/00268970903117126 fatcat:fawxuevotrh7hnrfivxfqkpab4

Solving Vehicle Routing Problem for Multistorey Buildings Using Iterated Local Search

2019 Turkish Journal of Electrical Engineering and Computer Sciences  
VRP can also be applied to the optimisation of delivering the packages (goods, meals, folders, mails, etc.) to rooms or locations of the structures such as buildings, and skyscrapers for travelling robots  ...  In this study, we defined and formulated the VRP in multistorey buildings (Multistorey VRP) for the first time and proposed a solving method employing iterated local search metaheuristic algorithm.  ...  Local search is another critical procedure of the algorithm; Algorithm 1 : 5 S 15 Iterated Local Search Metaheuristic 1 S ← construct initial solution; 2 S * ← apply local search to S ; 3 while termination  ... 
doi:10.3906/elk-1803-96 fatcat:drjpvkgysvhcjmufpskvpysznu

Comparison of Optimisation Algorithms for Deformable Template Matching [chapter]

Vasileios Zografos
2009 Lecture Notes in Computer Science  
In this work we examine in detail the use of optimisation algorithms on deformable template matching problems.  ...  We start with the examination of simple, direct-search methods and move on to more complicated evolutionary approaches.  ...  Additionally, they have been shown [16] to perform well in problems involving large search spaces due to their ability in locating goodenough solutions very early in the optimisation process.  ... 
doi:10.1007/978-3-642-10520-3_105 fatcat:owmvqac7rjhydcww5dyjbkb74i
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