Your selections:

9Gao, David
6Ruan, Ning
3Mammadov, Musa
2Banerjee, Arunava
2Chen, Yi
2Hanoun, Samer
2Nahavandi, Saeid
2Wu, Zhiyou
2Zhou, Xiaojun
1Ali, Mortuza
1Arafat, Jahidul
1Bhatti, Asim
1Chetty, Madhu
1Coppel, Ross
1Faruquzzaman, A. B. M.
1Gu, Yanhong
1Hurst, Cameron
1Khan, Burhan
1Li, Chaojie
1Nguyen, Vinh

Show More

Show Less

6Canonical duality theories
4Canonical duality theory
4Integer programming
3Maximization problem
3Optimization
3Problem solving
3Scheduling
20802 Computation Theory and Mathematics
2Adverse drug reaction
2Algorithms
2Canonical transformation
2Convex set
2Data processing
2Dual problem
2Dual transformation
2Integer optimization
2Multi-label classification
2Optimization techniques
2Scheduling algorithms

Show More

Show Less

Format Type

A multiobjective state transition algorithm for single machine scheduling

- Zhou, Xiaojun, Hanoun, Samer, Gao, David, Nahavandi, Saeid

**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.

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.

Intuitive haptics interface with accurate force estimation and reflection at nanoscale

- Bhatti, Asim, Khan, Burhan, Nahavandi, Saeid, Hanoun, Samer, Gao, David

**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**Reviewed:****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

- Zhou, Xiaojun, Gao, David, Yang, Chunhua

**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.

Solving facility location problem based on duality approach

**Authors:**Ruan, Ning**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. 165-172**Full Text:**false**Reviewed:****Description:**The facility location problem is one of the most widely studied discrete location problems, whose applications arise in a variety of settings, such as routers or servers in a communication network, warehouses or distribution centres in a supply chain, hospitals or airports in a public service system. The problem involves locating a number of facilities to minimize the sum of the fixed setup costs and the variable costs of serving the market demand from these facilities. First a dual problem is developed for the facility location problem. Then general optimality conditions are also obtained, which generate sequences globally converging to a primal and dual solutions, respectively. © Springer International Publishing Switzerland 2015.

An efficient classification using support vector machines

- Ruan, Ning, Chen, Yi, Gao, David

**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.

An interesting cryptography study based on knapsack problem

**Authors:**Ruan, Ning**Date:**2013**Type:**Text , Conference paper**Relation:**Proceedings - UKSim 15th International Conference on Computer Modelling and Simulation, UKSim 2013 p. 330-334**Full Text:****Reviewed:****Description:**Cryptography is an art that has been practised through the centuries. Interest in the applications of the knapsack problem to cryptography has arisen with the advent of public key cryptography. The knapsack problem is well documented problem and all research into its properties have lead to the conjecture that it is difficult to solve. In this paper the canonical duality theory is presented for solving general knapsack problem. By using the canonical dual transformation, the integer programming problem can be converted into a continuous canonical dual problem with zero duality gap. The optimality criterion are also discussed. Numerical examples show the efficiency of the method. Â© 2013 IEEE.

**Authors:**Ruan, Ning**Date:**2013**Type:**Text , Conference paper**Relation:**Proceedings - UKSim 15th International Conference on Computer Modelling and Simulation, UKSim 2013 p. 330-334**Full Text:****Reviewed:****Description:**Cryptography is an art that has been practised through the centuries. Interest in the applications of the knapsack problem to cryptography has arisen with the advent of public key cryptography. The knapsack problem is well documented problem and all research into its properties have lead to the conjecture that it is difficult to solve. In this paper the canonical duality theory is presented for solving general knapsack problem. By using the canonical dual transformation, the integer programming problem can be converted into a continuous canonical dual problem with zero duality gap. The optimality criterion are also discussed. Numerical examples show the efficiency of the method. Â© 2013 IEEE.

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.

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:****Reviewed:****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

**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:****Reviewed:****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

**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.

Polynomial time algorithm for learning globally optimal Dynamic Bayesian network

- Nguyen, Vinh, Chetty, Madhu, Coppel, Ross, Wangikar, Prangipar

**Authors:**Nguyen, Vinh , Chetty, Madhu , Coppel, Ross , Wangikar, Prangipar**Date:**2011**Type:**Text , Conference paper**Relation:**18th International Conference, ICONIP 2011. Shanghai, China, 13th-17th November, 2011 In Neural Information Processing. ICONIP 2011 (Lecture Notes in Computer Science) vol 7064. p 719-729**Full Text:**false**Reviewed:****Description:**This paper is concerned with the problem of learning the globally optimal structure of a dynamic Bayesian network (DBN). We propose using a recently introduced information theoretic criterion named MIT (Mutual Information Test) for evaluating the goodness-of-fit of the DBN structure. MIT has been previously shown to be effective for learning static Bayesian network, yielding results competitive to other popular scoring metrics, such as BIC/MDL, K2 and BD, and the well-known constraint-based PC algorithm. This paper adapts MIT to the case of DBN. Using a modified variant of MIT, we show that learning the globally optimal DBN structure can be efficiently achieved in polynomial time.**Description:**Lecture Notes in Computer Science, vol 7064.

A new technique for global optimization methods

**Authors:**Wu, Zhiyou , Pang, Xianglu**Date:**2010**Type:**Text , Conference paper**Relation:**Paper presented at 1st International Conference on Green Circuits and Systems, ICGCS 2010, Shanghai : 21st-23rd June 2010 p. 398-403**Full Text:**false**Description:**We know that the necessary local optimality conditions are the main tools for the development of efficient numerical methods in local optimization. In this paper, we propose a new technique for global optimization methods. First we will introduce some new approach to obtain some verifiable global optimality conditions including some necessary global optimality conditions and some sufficient global optimality conditions. Then we will introduce how to use the obtained necessary global optimality conditions to design a new optimization method called strongly local optimization method and combining the new strongly local optimization method, some methods to improve the current strongly local minimizer and the obtained sufficient global optimality conditions to design some global optimization methods with some stopping criteria. © 2010 IEEE.

Literature on image segmentation based on split - and - Merge techniques

- Faruquzzaman, A. B. M., Paiker, Nafize, Arafat, Jahidul, Ali, Mortuza, Sorwar, Golam

**Authors:**Faruquzzaman, A. B. M. , Paiker, Nafize , Arafat, Jahidul , Ali, Mortuza , Sorwar, Golam**Date:**2008**Type:**Text , Conference proceedings , Conference paper**Relation:**ICITA 2008, Cairns, Qld., 23-26 June, ICITA, published in Proceedings of 5th International Conference on Information Technology and Application pp. 120-125.**Full Text:**false**Reviewed:****Description:**Image segmentation is a feverish issue due to drastically increasing the use of computer and the Internet. Various algorithms have been invented on this aspect. Among them, split-and-merge (SM) algorithm is highly lucrative now-a-days due to its simplicity and effectiveness in the sector of image processing. Numerous researchers have performed their research work on this algorithm to triumph over its drawbacks for its sustainable and competent implementation. This paper has consolidated the useful consideration and proposal of various researchers to formulate a strong base of knowledge for the future researcher. It has also tinted few unsettled drawbacks of SM algorithm which will open the casement of brainstorming as well as persuade them for future research on SM algorithm, thereby allow SM algorithm to attain a globally optimal algorithm for image segmentation.**Description:**5th International Conference on Information Technology and Applications, ICITA 2008

A recursive digital filter design using global optimization technique

**Authors:**Wu, Zhiyou , Gu, Yanhong**Date:**2006**Type:**Text , Conference paper**Relation:**Paper presented at APCCAS 2006, IEEE Asia Pacific Conference on Circuits and Systems, Singapore : 4th December, 2006**Full Text:**false**Reviewed:****Description:**Close form analytical techniques for the design of a certain class of recursive digital filters such as the elliptic filter have appeared. Such close form analytical techniques are suitable for designing filters with piece-wise constant magnitude response. The design of recursive digital filters with arbitrary frequency response is a nonlinear optimization problem. Specifically, it belongs to the class of global bi-lever programming problem. Optimal solution for a global bi-lever programming problem is notoriously difficult to obtain. In this paper, the bi-lever programming problem is first converted into a differentiate one-lever problem. Consequently we not only prove that the global minimizer of the converted one-lever problem is an approximate global minimizer of the original bi-lever problem, but also a novel filled function method for the design of recursive digital filters meeting arbitrary frequency response specifications is proposed. Several design examples are presented to illustrate our new technique**Description:**E1**Description:**2003001898

- Tilakaratne, Chandima, Mammadov, Musa, Hurst, Cameron

**Authors:**Tilakaratne, Chandima , Mammadov, Musa , Hurst, Cameron**Date:**2006**Type:**Text , Conference paper**Relation:**Paper presented at Integrating AI and Data Mining, 1st International Workshop Proceedings, Hobart, Tasmania : 4th - 5th December, 2006**Full Text:**false**Reviewed:****Description:**This study investigates how intermarket influences can be used to help the prediction of the direction (up or down) of the next day's close price of the Australian All Ordinary Index (AORD). First, intermarket influences from the potential influential markets on the AORD are quantified by assigning weights for all influential markets. The weights were defined as a solution to an optimization problem which aims to maximise rank correlation between the current day's relative return of the AORD and the weighted sum of lagged relative returns of the potential influential markets. Then, the next day's relative return of the AORD is predicted by applying the neural networks as a classifier. Two different scenarios were compared: 1) using the current day's relative returns of different sets of influential markets as separate inputs; and, 2) using only the weighted sum of these relative returns as a "combined market". The results revealed that the second approach provides better predictions in all cases. This shows the effectiveness of the proposed approach for quantifying intermarket influences and the potential of using the "weighted combined markets" for the prediction**Description:**E1**Description:**2003001609

An optimization approach to identifying drugs responsible for adverse drug reactions

- Mammadov, Musa, Banerjee, Arunava

**Authors:**Mammadov, Musa , Banerjee, Arunava**Date:**2005**Type:**Text , Conference paper**Relation:**Paper pesented at Sixteenth Australasian Workshop on Combinatorial Algorithms, AWOCA 2005, Ballarat, Victoria : 18th-21st September 2005 p. 185-200**Full Text:**false**Description:**In this paper we develop an optimization approach for the study of Adverse Drug Reaction (ADR) problems. This approach is based on drug-reaction relationships represented in the form of a vector weights, which can be defined as a solution to some global optimization problem. Although it can be used for solving many ADR problems, we concentrate on the problem of accurate identification of drugs that are responsible for reactions that have occurred. Based on drug-reaction relationships, we formulate this problem as an optimization problem. The approach is applied to Australian Adverse Drug Reaction Advisory Committee (ADRAC) database. We take a comprehensive approach to considering all reaction classes which combines 18 SOC (System Organ Class), as well as the sub-classes of reaction classes Blood, Body, Neurological and Cardiovascular. The numerical experiments provided high accuracy in prediction of suspected drugs reported in ADRAC database.**Description:**2003001383

An optimization approach to the study of drug-drug interactions

- Mammadov, Musa, Banerjee, Arunava

**Authors:**Mammadov, Musa , Banerjee, Arunava**Date:**2005**Type:**Text , Conference paper**Relation:**Paper pesented at Sixteenth Australasian Workshop on Combinatorial Algorithms, AWOCA 2005, Ballarat, Victoria : 18th-21st September 2005 p. 201-216**Full Text:****Description:**Drug-drug interaction is one of the important problems of Adverse Drug Reaction (ADR). In this paper we develop an optimization approach for the study of this problem. This approach is based on drug-reaction relationships represented in the form of a vector of weights, which can be defined as a solution to some global optimization problem. Although this approach can be used for solving many ADR problems, we concentrate here only on drug-drug interactions. Based on drug-reaction relationships, we formulate this problem as an optimization problem. The approach is applied to different classes of reactions from the Australian Adverse Drug Reaction Advisory Committee (ADRAC) database.**Description:**2003001384

**Authors:**Mammadov, Musa , Banerjee, Arunava**Date:**2005**Type:**Text , Conference paper**Relation:**Paper pesented at Sixteenth Australasian Workshop on Combinatorial Algorithms, AWOCA 2005, Ballarat, Victoria : 18th-21st September 2005 p. 201-216**Full Text:****Description:**Drug-drug interaction is one of the important problems of Adverse Drug Reaction (ADR). In this paper we develop an optimization approach for the study of this problem. This approach is based on drug-reaction relationships represented in the form of a vector of weights, which can be defined as a solution to some global optimization problem. Although this approach can be used for solving many ADR problems, we concentrate here only on drug-drug interactions. Based on drug-reaction relationships, we formulate this problem as an optimization problem. The approach is applied to different classes of reactions from the Australian Adverse Drug Reaction Advisory Committee (ADRAC) database.**Description:**2003001384

Optimisation solvers and problem formulations for solving a data clustering problem

**Authors:**Ugon, Julien , Rubinov, Alex**Date:**2005**Type:**Text , Conference paper**Relation:**Paper presented at the Sixteenth Australasian Workshop on Combinatorial Algorithms, Ballarat, Victoria : 18th - 21st September, 2005**Full Text:****Reviewed:****Description:**A popular apprach for solving complex optimization problems is through relaxation: some constraints are removed in order to have a convex problem approximating the original problem. On the other hand, direct approaches for solving such problems are becoming increasingly powerful. This paper examines two cases drawn from data analysis, in order to compare the two techniques.**Description:**E1**Description:**2003001437

**Authors:**Ugon, Julien , Rubinov, Alex**Date:**2005**Type:**Text , Conference paper**Relation:**Paper presented at the Sixteenth Australasian Workshop on Combinatorial Algorithms, Ballarat, Victoria : 18th - 21st September, 2005**Full Text:****Reviewed:****Description:**A popular apprach for solving complex optimization problems is through relaxation: some constraints are removed in order to have a convex problem approximating the original problem. On the other hand, direct approaches for solving such problems are becoming increasingly powerful. This paper examines two cases drawn from data analysis, in order to compare the two techniques.**Description:**E1**Description:**2003001437

- «
- ‹
- 1
- ›
- »

Are you sure you would like to clear your session, including search history and login status?