On abstract convexity and set valued analysis
- Authors: Burachik, Regina , Rubinov, Alex
- Date: 2008
- Type: Text , Journal article
- Relation: Journal of Nonlinear and Convex Analysis Vol. 9, no. 1 (2008), p. 105-123
- Full Text: false
- Reviewed:
- Description: Given a set L subset of R-X of functions defined on X, we consider abstract monotone (or, for short, L-monotone) multivalued operators T : X paired right arrows L. We extend the definition of enlargement of monotone operators to this framework and study semicontinuity properties of these mappings. We prove that sequential outer semicontinuity, which holds for maximal monotone operators and their enlargements in the classical case (i.e., when L = X* and X is a Banach space), holds also in our abstract setting. We also show through examples that some properties, known to hold in the classical case, may no longer be valid in the abstract setting. One of these properties is the maximality of the subdifferential and another one is the lack of inner semicontinuity of (point-to-set) monotone operators in the interior of their domain. We also focus on the structure of both the abstract subdifferential and the abstract epsilon-subdifferential. This is a key question in abstract convexity because these sets may be very large for certain choices of L and therefore it is important to be able to represent them by means of some special elements of the set of "affine" functions induced by L.
On augmented lagrangians for optimization problems with a single constraint
- Authors: Gasimov, Rafail , Rubinov, Alex
- Date: 2004
- Type: Text , Journal article
- Relation: Journal of Global Optimization Vol. 28, no. 2 (2004), p. 153-173
- Full Text: false
- Reviewed:
- Description: We examine augmented Lagrangians for optimization problems with a single (either inequality or equality) constraint. We establish some links between augmented Lagrangians and Lagrange-type functions and propose a new kind of Lagrange-type functions for a problem with a single inequality constraint. Finally, we discuss a supergradient algorithm for calculating optimal values of dual problems corresponding to some class of augmented Lagrangians.
- Description: C1
- Description: 2003000929
On global optimality conditions via separation functions
- Authors: Rubinov, Alex , Uderzo, A.
- Date: 2001
- Type: Text , Journal article
- Relation: Journal of Optimization Theory and Applications Vol. 109, no. 2 (May 2001), p. 345-370
- Full Text: false
- Reviewed:
- Description: The paper examines some axiomatic definitions of separation functions that can be employed fruitfully in the analysis of side-constrained extremum problems. A study of their general properties points out connections with abstract convex analysis and recent generalizations of Lagrangian approaches to duality and exact penalty methods. Many concrete examples are brought out.
On the absence of duality gap for Lagrange-type functions
- Authors: Rubinov, Alex , Burachik, Regina
- Date: 2005
- Type: Text , Journal article
- Relation: Journal of Industrial and Management Optimization Vol. 1, no. 1 (2005), p. 33-38
- Full Text:
- Reviewed:
- Description: Given a generic dual program we discuss the absence of duality gap for a family of Lagrange-type functions. We obtain necessary conditions that become sufficient ones under some additional assumptions. We also give examples of Lagrangetype functions for which this sufficient conditions hold.
- Description: C1
- Description: 2003001425
Optimal placement of access point in WLAN based on a new algorithm
- Authors: Kouhbor, Shahnaz , Ugon, Julien , Kruger, Alexander , Rubinov, Alex
- Date: 2005
- Type: Text , Conference paper
- Relation: Paper presented at ICMB 2005, International Conference on Mobile Business, Sydney, Australia, 11-13 July 2005, Sydney : 11th - 13th July, 2005
- Full Text:
- Reviewed:
- Description: When designing wireless communication systems, it is very important to know the optimum numbers and locations for the access points (APs). The impact of incorrect placement of APs is significant. If they are placed too far apart, they will generate a coverage gap, but if they are too close to each other, this will lead to excessive co-channel interferences. In this paper we describe a mathematical model developed to find the optimal number and location of APs. To solve the problem, we use the Discrete Gradient optimization algorithm developed at the University of Ballarat. Results indicate that our model is able to solve optimal coverage problems for different numbers of users.
- Description: 2003001377
Optimality conditions in global optimization and their applications
- Authors: Rubinov, Alex , Wu, Zhiyou
- Date: 2009
- Type: Text , Journal article
- Relation: Mathematical Programming Vol. 120, no. 1 SPEC. ISS. (2009), p. 101-123
- Full Text: false
- Reviewed:
- Description: In this paper we derive necessary and sufficient conditions for some problems of global minimization. Our approach is based on methods of abstract convexity: we use a representation of an upper semicontinuous function as the lower envelope of a family of convex functions. We discuss applications of conditions obtained to the examination of some tractable sufficient conditions for the global minimum and to the theory of inequalities. © 2007 Springer-Verlag.
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
Optimization approach for clustering datasets with weights
- Authors: Ghosh, Ranadhir , Rubinov, Alex , Zhang, Jiapu
- Date: 2005
- Type: Text , Journal article
- Relation: Optimization Methods & Software Vol. 20, no. 2-3 (Apr-Jun 2005), p. 329-345
- Full Text:
- Reviewed:
- Description: We introduce datasets with weights and suggest using the minimization of some highly nonsmooth functions for clustering of such datasets. Datasets with weights often appear as the result of an approximation of large-scale datasets. We examine such approximations and also consider the application of datasets with weights to examine self-organizing maps. Results of some numerical experiments are presented and discussed.
- Description: C1
- Description: 2003001366
Optimization based clustering algorithms in multicast group hierarchies
- Authors: Jia, Long , Ouveysi, Iradj , Rubinov, Alex , Bagirov, Adil
- Date: 2003
- Type: Text , Conference paper
- Relation: Paper presented at the 2003 Australian Telecommunications Networks and Applications Conference, Melbourne : 8th - 10th December, 2003
- Full Text:
- Reviewed:
- Description: In this paper we propose the use of optimization based clustering algorithms to determine hierarchical multicast trees. This problem is formulated as an optimization problem with a non-smooth, non-convex objective function. Different algorithms are examined for solving this problem. Results of numerical experiments using some artificial and real-world databases are reported. We compare several optimization based clustering methods and their combinations with the k- means method. The results demonstrate the effectiveness of these algorithms.
- Description: E1
- Description: 2003000382
Optimization in data mining
- Authors: Karasozen, Bulent , Rubinov, Alex , Weber, Gerhard-Wilhelm
- Date: 2006
- Type: Text , Journal article
- Relation: European Journal of Operational Research Vol. 173, no. 3 (2006), p. 701-704
- Full Text: false
- Reviewed:
- Description: C1
Optimization in telecommunication network maintenance
- Authors: Jia, Long , Rubinov, Alex , Ouveysi, Iradj
- Date: 2003
- Type: Text , Conference paper
- Relation: Paper presented at the Symposium on Industrial Optimisation and the 9th Australian Optimisation Day, Perth : 30th September, 2002
- Full Text: false
- Reviewed:
- Description: E1
- Description: 2003000349
Optimization in wireless local area network
- Authors: Kouhbor, Shahnaz , Ugon, Julien , Kruger, Alexander , Rubinov, Alex , Branch, Philip
- Date: 2004
- Type: Text , Conference paper
- Relation: Paper presented at ICOTA6: 6th International Conference on Optimization - Techniques and Applications, Ballarat, Victoria : 9th December, 2004
- Full Text: false
- Reviewed:
- Description: 2003000886
Penalty functions with a small penalty parameter
- Authors: Rubinov, Alex , Yang, Xiao , Bagirov, Adil
- Date: 2002
- Type: Text , Journal article
- Relation: Optimization Methods and Software Vol. 17, no. 5 (2002), p. 931-964
- Full Text: false
- Reviewed:
- Description: In this article, we study the nonlinear penalization of a constrained optimization problem and show that the least exact penalty parameter of an equivalent parametric optimization problem can be diminished. We apply the theory of increasing positively homogeneous (IPH) functions so as to derive a simple formula for computing the least exact penalty parameter for the classical penalty function through perturbation function. We establish that various equivalent parametric reformulations of constrained optimization problems lead to reduction of exact penalty parameters. To construct a Lipschitz penalty function with a small exact penalty parameter for a Lipschitz programming problem, we make a transformation to the objective function by virtue of an increasing concave function. We present results of numerical experiments, which demonstrate that the Lipschitz penalty function with a small penalty parameter is more suitable for solving some nonconvex constrained problems than the classical penalty function.
- Description: 2003000116
Penalty functions with a small penalty parameter : Numerical experiments
- Authors: Bagirov, Adil , Rubinov, Alex
- Date: 2003
- Type: Text , Conference paper
- Relation: Paper presented at Industrial Optimization Conference 2003, Perth : 30th September, 2002
- Full Text: false
- Reviewed:
- Description: E1
- Description: 2003000432
Scalarization and nonlinear scalar duality for vector optimization with preferences that are not necessarily a pre-order relation
- Authors: Rubinov, Alex , Gasimov, Rafail
- Date: 2004
- Type: Text , Journal article
- Relation: Journal of Global Optimization Vol. 29, no. 4 (2004), p. 455-477
- Full Text: false
- Reviewed:
- Description: We consider problems of vector optimization with preferences that are not necessarily a pre-order relation. We introduce the class of functions which can serve for a scalarization of these problems and consider a scalar duality based on recently developed methods for non-linear penalization scalar problems with a single constraint.
- Description: C1
- Description: 2003000932
Separation in B-convexity
- Authors: Rubinov, Alex , Briec, W. , Horvath, C. D
- Date: 2005
- Type: Text , Journal article
- Relation: Journal of Global Optimization Vol. 1, no. 1 (2005), p. 13-30
- Full Text: false
- Reviewed:
- Description: A subset B of R
- Description: C1
- Description: 2003001426
Sigma-porosity in monotonic analysis with applications to optimization
- Authors: Rubinov, Alex
- Date: 2005
- Type: Text , Journal article
- Relation: Abstract and Applied Analysis Vol. 2005, no. 3 (2005), p. 287-305
- Full Text: false
- Reviewed:
- Description: We introduce and study some metric spaces of increasing positively homogeneous (IPH) functions, decreasing functions, and conormal (upward) sets. We prove that the complements of the subset of strictly increasing IPH functions, of the subset of strictly decreasing functions, and of the subset of strictly conormal sets are $sigma$-porous in corresponding spaces. Some applications to optimization are given.
- Description: C1
- Description: We introduce and study some metric spaces of increasing positively homogeneous (IPH) functions, decreasing functions, and conormal (upward) sets. We prove that the complements of the subset of strictly increasing IPH functions, of the subset of strictly decreasing functions, and of the subset of strictly conormal sets are $\sigma$-porous in corresponding spaces. Some applications to optimization are given.
- Description: 2003001421
Some nonlinear Lagrange and penalty functions for problems with a single constraint
- Authors: Giri, Jason , Rubinov, Alex
- Date: 2009
- Type: Text , Book chapter
- Relation: Optimization : Structure and applications Chapter 3 p. 41-54
- Full Text: false
- Description: 2003007561
Stability of semi-infinite inequality systems involving min-type functions
- Authors: López, Marco , Rubinov, Alex , Vera De Serio, Virginia
- Date: 2005
- Type: Text , Journal article
- Relation: Numerical Functional Analysis and Optimization Vol. 26, no. 1 (2005), p. 81-112
- Full Text: false
- Reviewed:
- Description: We study the stability of semi-infinite inequality systems that arise in monotonic analysis. These systems are defined by certain classes of abstract linear functions. We consider the cone R
- Description: C1
- Description: 2003001420
Stability of the lower level sets of ICAR functions
- Authors: López, Marco , Rubinov, Alex , Vera De Serio, Virginia
- Date: 2005
- Type: Text , Journal article
- Relation: Numerical Functional Analysis and Optimization Vol. 26, no. 1 (2005), p. 113-127
- Full Text: false
- Reviewed:
- Description: In this paper, we study the stability of the lower level set {x E R++n | f (x) ≤ 0} of a finite valued increasing convex-along-rays (ICAR) function f defined on R++n. In monotonic analysis, ICAR functions play the role of usual convex functions in classical convex analysis. We show that each ICAR function f is locally Lipschitz on int dom f and that the pointwise convergence of a sequence of ICAR functions implies its uniform convergence on each compact subset of R ++n. The latter allows us to establish stability results for ICAR functions in some sense similar to those for convex functions. Copyright © Taylor & Francis, Inc.
- Description: C1
- Description: 2003001419