A multiobjective state transition algorithm for single machine scheduling
- Authors: Zhou, Xiaojun , Hanoun, Samer , Gao, David , Nahavandi, Saeid
- Date: 2015
- Type: Text , Conference paper
- Relation: 3rd World Congress on Global Optimization in Engineering and Science, WCGO 2013; Anhui, China; 8th-12th July 2013 Vol. 95, p. 79-88
- Full Text: false
- Reviewed:
- Description: In this paper, a discrete state transition algorithm is introduced to solve a multiobjective single machine job shop scheduling problem. In the proposed approach, a non-dominated sort technique is used to select the best from a candidate state set, and a Pareto archived strategy is adopted to keep all the non-dominated solutions. Compared with the enumeration and other heuristics, experimental results have demonstrated the effectiveness of the multiobjective state transition algorithm. © Springer International Publishing Switzerland 2015.
Advances in Global Optimization
- Authors: Gao, David , Ruan, Ning , Xing, Wenxun
- Date: 2015
- Type: Text , Conference paper
- Relation: 3rd World Congress on Global Optimization in Engineering and Science, WCGO 2013; Anhui, China; 8th-12th July 2013 Vol. 95
- Full Text: false
- Reviewed:
- Description: This proceedings volume addresses advances in global optimization - a multidisciplinary research field that deals with the analysis, characterization, and computation of global minima and/or maxima of nonlinear, non-convex, and nonsmooth functions in continuous or discrete forms. The volume contains selected papers from the third biannual World Congress on Global Optimization in Engineering & Science (WCGO), held in the Yellow Mountains, Anhui, China on July 8-12, 2013. The papers fall into eight topical sections: mathematical programming; combinatorial optimization; duality theory; topology optimization; variational inequalities and complementarity problems; numerical optimization; stochastic models and simulation; and complex simulation and supply chain analysis.
Application of canonical duality theory to fixed point problem
- Authors: Ruan, Ning , Gao, David
- Date: 2015
- Type: Text , Conference paper
- Relation: 3rd World Congress on Global Optimization in Engineering and Science, WCGO 2013; Anhui, China; 8th-12th July 2013 Vol. 95, p. 157-163
- Full Text: false
- Reviewed:
- Description: In this paper, we study general fixed point problem. We first rewrite the original problem in the canonical framework. Then, we proposed a canonical transformation of this problem, which leads to a convex differentiable dual problem and new iteration method. An illustrative example is presented. © Springer International Publishing Switzerland 2015.
Dynamical analysis of neural networks with time-varying delays using the LMI approach
- Authors: Lakshmanan, Shanmugam , Lim, Cheepeng , Bhatti, Asim , Gao, David , Nahavandi, Saeid
- Date: 2015
- Type: Text , Conference paper
- Relation: 22nd International Conference on Neural Information Processing, ICONIP 2015; Istanbul, Turkey; 9th-12th November 2015 Vol. 9491, p. 297-305
- Full Text: false
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- Description: This study is concerned with the delay-range-dependent stability analysis for neural networks with time-varying delay and Markovian jumping parameters. The time-varying delay is assumed to lie in an interval of lower and upper bounds. The Markovian jumping parameters are introduced in delayed neural networks, which are modeled in a continuous-time along with finite-state Markov chain. Moreover, the sufficient condition is derived in terms of linear matrix inequalities based on appropriate Lyapunov-Krasovskii functionals and stochastic stability theory, which guarantees the globally asymptotic stable condition in the mean square. Finally, a numerical example is provided to validate the effectiveness of the proposed conditions. © Springer International Publishing Switzerland 2015.
Intuitive haptics interface with accurate force estimation and reflection at nanoscale
- Authors: Bhatti, Asim , Khan, Burhan , Nahavandi, Saeid , Hanoun, Samer , Gao, David
- Date: 2015
- Type: Text , Conference paper
- Relation: 3rd World Congress on Global Optimization in Engineering and Science, WCGO 2013; Anhui, China; 8th-12th July 2013 Vol. 95, p. 507-514
- Full Text: false
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- Description: Technologies, such as Atomic Force Microscopy (AFM), have proven to be one of the most versatile research equipments in the field of nanotechnology by providing physical access to the materials at nanoscale. Working principles of AFM involve physical interaction with the sample at nanometre scale to estimate the topography of the sample surface. Size of the cantilever tip, within the range of few nanometres diameter, and inherent elasticity of the cantilever allow it to bend in response to the changes in the sample surface leading to accurate estimation of the sample topography. Despite the capabilities of the AFM, there is a lack of intuitive user interfaces that could allow interaction with the materials at nanoscale, analogous to the way we are accustomed to at macro level. To bridge this gap of intuitive interface design and development, a haptics interface is designed in conjunction with Bruker Nanos AFM. Interaction with the materials at nanoscale is characterised by estimating the forces experienced by the cantilever tip employing geometric deformation principles. Estimated forces are reflected to the user, in a controlled manner, through haptics interface. Established mathematical framework for force estimation can be adopted for AFM operations in air as well as in liquid mediums. © Springer International Publishing Switzerland 2015.
Model modification in scheduling of batch chemical processes
- Authors: Zhou, Xiaojun , Gao, David , Yang, Chunhua
- Date: 2015
- Type: Text , Conference paper
- Relation: 3rd World Congress on Global Optimization in Engineering and Science, WCGO 2013; Anhui, China; 8th-12th July 2013 Vol. 95, p. 89-97
- Full Text: false
- Reviewed:
- Description: This paper addresses the model modification in scheduling of batch chemical processes, which is widely used in current literatures. In the modified model, the capacity, storage constraints are modified and the allocation, sequence constraints are simplified. It is shown that the modified model can lead to fewer decision variables, fewer constraints, resulting in low computational complexity. Experimental results with two classical examples are given to demonstrate the effectiveness of the proposed formulation and approach. © Springer International Publishing Switzerland 2015.
NP-hard problems in computational large deformation mechanics and canonical dual finite element method
- Authors: Ruan, Ning , Gao, David
- Date: 2014
- Type: Text , Conference paper
- Relation: Proceedings of the 11th World Congress on Computational Mechanics (WCCM XI) p. 1-2
- Full Text: false
- Reviewed:
An efficient classification using support vector machines
- Authors: Ruan, Ning , Chen, Yi , Gao, David
- Date: 2013
- Type: Text , Conference paper
- Relation: Proceedings of 2013 Science and Information Conference, SAI 2013 p. 585-589
- Full Text: false
- Reviewed:
- Description: Support vector machine (SVM) is a popular method for classification in data mining. The canonical duality theory provides a unified analytic solution to a wide range of discrete and continuous problems in global optimization. This paper presents a canonical duality approach for solving support vector machine problem. It is shown that by the canonical duality, these nonconvex and integer optimization problems are equivalent to a unified concave maximization problem over a convex set and hence can be solved efficiently by existing optimization techniques. © 2013 The Science and Information Organization.
Canonical dual approach for minimizing a nonconvex quadratic function over a sphere
- Authors: Chen, Yi , Gao, David
- Date: 2013
- Type: Text , Conference paper
- Relation: 3rd World Congress on Global Optimization in Engineering and Science, WCGO 2013; Anhui, China; 8th-12th July 2013 Vol. 95, p. 149-156
- Full Text: false
- Reviewed:
- Description: In this paper, we study global optimal solutions of minimizing a nonconvex quadratic function subject to a sphere constraint. The main challenge is to solve the problem when it has multiple global solutions on the boundary of the sphere, which is called hard case. By canonical duality theory, a concave maximization problem is formulated, which is one-dimensional and without duality gaps to the primal problem. Then sufficient and necessary conditions are provided to identify whether the problem is in the hard case or not. A perturbation method and associated algorithms are proposed to solve hard-case problems. Theoretical results and methods are verified by numerical examples. © Springer International Publishing Switzerland 2015.
Video driven traffic modelling
- Authors: Zhou, Hailing , Creighton, Douglas , Wei, Lei , Gao, David , Nahavandi, Saeid
- Date: 2013
- Type: Text , Conference paper
- Relation: 2013 IEEE/ASME International Conference on Advanced Intelligent Mechatronics: Mechatronics for Human Wellbeing, AIM 2013 p. 506-511
- Full Text: false
- Reviewed:
- Description: We propose Video Driven Traffic Modelling (VDTM) for accurate simulation of real-world traffic behaviours with detailed information and low-cost model development and maintenance. Computer vision techniques are employed to estimate traffic parameters. These parameters are used to build and update a traffic system model. The model is simulated using the Paramics traffic simulation platform. Based on the simulation techniques, effects of traffic interventions can be evaluated in order to achieve better decision makings for traffic management authorities. In this paper, traffic parameters such as vehicle types, times of starting trips and corresponding origin-destinations are extracted from a video. A road network is manually defined according to the traffic composition in the video, and individual vehicles associated with extracted properties are modelled and simulated within the defined road network using Paramics. VDTM has widespread potential applications in supporting traffic decision-makings. To demonstrate the effectiveness, we apply it in optimizing a traffic signal control system, which adaptively adjusts green times of signals at an intersection to reduce traffic congestion.
- Description: E1
Video driven traffic modelling in paramics
- Authors: Zhou, Hailing , Creighton, Douglas , Lim, Cheepeng , Wei, Lei , Gao, David
- Date: 2013
- Type: Text , Conference paper
- Relation: Proceedings - UKSim 15th International Conference on Computer Modelling and Simulation, UKSim 2013 p. 525-530
- Full Text: false
- Reviewed:
- Description: With urbanization and vehicle availability, there exist many traffic problems including congestion, environmental impact and safety. In order to address these problems, we propose a video driven traffic modelling system in this paper. The system can simulate real-world traffic activities in a computer, based on traffic data recorded in videos. Video processing is employed to estimate metrics such as traffic volumes. These metrics are used to update the traffic system model, which is then simulated using the ParamicsTM traffic simulation platform. Video driven traffic modelling has widespread potential application in traffic systems, due to the convenience and reduced costs of model development and maintenance. Experiments are conducted in this paper to demonstrate the effectiveness of the proposed system. © 2013 IEEE.
- Description: 2003011214
Canonical duality theory and algorithm for solving challenging problems in network optimisation
- Authors: Ruan, Ning , Gao, David
- Date: 2012
- Type: Text , Conference paper
- Relation: 19th International Conference on Neural Information Processing, ICONIP 2012 Vol. 7665 LNCS, p. 702-709
- Full Text:
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- Description: This paper presents a canonical dual approach for solving a general nonconvex problem in network optimization. Three challenging problems, sensor network location, traveling salesman problem, and scheduling problem are listed to illustrate the applications of the proposed method. It is shown that by the canonical duality, these nonconvex and integer optimization problems are equivalent to unified concave maximization problem over a convex set and hence can be solved efficiently by existing optimization techniques. © 2012 Springer-Verlag.
- Description: 2003010653
Global minimizer of large scale stochastic rosenbrock function : canonical duality approach
- Authors: Li, Chaojie , Gao, David
- Date: 2012
- Type: Text , Conference paper
- Relation: 19th International Conference on Neural Information Processing, ICONIP 2012 Vol. 7666 LNCS, p. 677-682
- Full Text:
- Reviewed:
- Description: Canonical duality theory for solving the well-known benchmark test problem of stochastic Rosenbrock function is explored by two canonical transformations. Global optimality criterion is analytically obtained, which shows that the stochastic disturbance of these parameters could be eliminated by a proper canonical dual transformation. Numerical simulations illustrate the canonical duality theory is potentially powerful for solving this benchmark test problem and many other challenging problems in global optimization and complex network systems. © 2012 Springer-Verlag.
- Description: 2003010651
Global optimal solutions to nonconvex euclidean distance geometry problems
- Authors: Ruan, Ning , Gao, David
- Date: 2012
- Type: Text , Conference paper
- Relation: 20th International Symposium on Mathematical Theory of Networks and Systems
- Full Text: false
- Reviewed:
- Description: This paper presents a canonical dual approach for solving nonconvex minimization problems in Euclidean distance geometry. The variant of this problem arises extensively in engineering and science, including computational biology, sensor network communications, database analysis, information technology, and global optimization. Due to the nonconvexity, most of these problems are NP-hard and traditional convex optimization methods can not be used directly for finding global optimal solutions. We first show that this type of nonconvex problems can be transferred to a concave maximization problem over a convex set. Then a general analytical solution is proposed by using the canonical duality theory. Applications are illustrated by network localization and minimization of Rosenbrock function. Furthermore, by using a perturbed canonical dual approach, a class of Euclidean distance problems can be converted to a unified concave maximization dual problem with zero duality gap, which can be solved by well-developed convex minimization methods.
Impulsive synchronization of state delayed discrete complex networks with switching topology
- Authors: Li, Chaojie , Gao, David , Liu, Chao
- Date: 2012
- Type: Text , Conference paper
- Relation: 19th International Conference on Neural Information Processing, ICONIP 2012 Vol. 7665 LNCS, p. 50-57
- Full Text:
- Reviewed:
- Description: In this paper, global exponential synchronization of a class of discrete delayed complex networks with switching topology is investigated by using Lyapunov-Ruzimiki method. The impulsive scheme is designed to work at the time instant of switching occurrence. A time-varying delay dependent criterion for impulsive synchronization is given to ensure the delayed discrete complex networks switching topology tending to a synchronous state. Furthermore, a numerical simulation is given to illustrate the effectiveness of main results. © 2012 Springer-Verlag.
- Description: 2003010652
Canonical dual approach to binary factor analysis
- Authors: Ke, Sun , Shikui, Tui , Gao, David , Xu, Lei
- Date: 2009
- Type: Text , Conference paper
- Relation: 8th International conference on Independent Component Analysis and Signal Separation. p. 346-353
- Full Text: false
- Reviewed:
- Description: Binary Factor Analysis (BFA) is a typical problem of Independent Component Analysis (ICA) where the signal sources are binary. Parameter learning and model selection in BFA are computationally intractable because of the combinatorial complexity. This paper aims at an efficient approach to BFA. For parameter learning, an unconstrained binary quadratic programming (BQP) is reduced to a canonical dual problem with low computational complexity; for model selection, we adopt the Bayesian Ying-Yang (BYY) framework to make model selection automatically during learning. In the experiments, the proposed approach cdual shows superior performance. Another BQP approximation round is also good in model selection and is more efficient. Two other methods, greedy and enum, are more accurate in BQP but fail to compete with cdual and round in BFA. We conclude that a good optimization is essential in a learning process, but the key task of learning is not simply optimization and an over-accurate optimization may not be preferred.