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Hybrid journal (It can contain Open Access articles)
ISSN (Print) 1570-1166 - ISSN (Online) 1572-9214
• Efficiency Improvement Strategy Under Constant Sum of Inputs
• Abstract: Abstract In this paper, we have formulated Data Envelopment Analysis (DEA) models to reduce the inputs in an inefficient Decision Making Unit (DMU) when the specific inputs are under the constant sum constraint. We have also extended the models to reallocate the excess input without any reduction in efficiency of other DMUs. These DEA models and methods developed in this work will help decision makers in developing an optimal strategy to transfer excess input to other DMUs. Theoretical results have been illustrated with the help of a case study.
PubDate: 2014-01-16

• Wolfe Type Higher Order Multiple Objective Nondifferentiable Symmetric
Dual Programming with Generalized Invex Function
• Abstract: Abstract In this paper, a new class of higher order (ϕ, ρ)-invex function is introduced with an example, in which the sublinearity and convexity assumption on ϕ with respect to third argument is relaxed. A pair of higher order Wolfe type multiobjective symmetric dual for a class of nondifferentiable multiobjective programming involving square root term is presented and the weak duality, strong duality and converse duality theorems are established with their proofs under higher order (ϕ, ρ)-invexity and (ϕ, ρ)-incavity assumption. Self duality theorem is proved for the proposed dual program. These results are used to discuss Wolfe type higher-order symmetric minimax mixed integer dual problems. A numerical example is developed where the results of weak and strong duality theorems can be applied. Discussion on some particular cases shows that our results generalize earlier results in related domain.
PubDate: 2014-01-12

• A Large-Update Interior-Point Method for Cartesian        class="a-plus-plus">P        class="a-plus-plus">∗(       class="a-plus-plus">κ)-LCP Over Symmetric
Cones
• Abstract: Abstract In this paper, we propose a new large-update interior point algorithm for the Cartesian P ∗(κ) linear complementarity problem over symmetric cones (SCLCP) based on a parametric kernel function, which determines both search directions and the proximity measure between the iterate and the μ-center. Using Euclidean Jordan algebras, we derive the iteration bound that match the currently best known iteration bound for large update methods.
PubDate: 2014-01-11

• Optimal SVM Classification for Compact Polarimetric Data Using Stokes
Parameters
• Abstract: Abstract In this paper, our objective is twofold: first, to assess the potential of the new compact polarimetry imaging radar system called hybrid-polarimetry (CL-pol): circular transmitted polarization and coherent dual linear receive polarizations for full characterization and exploitation of the backscattered field. Useful characteristics that are unique to the hybrid-polarity architecture are invariance to geometrical orientations and minimizing on-board resource requirements. Second, to develop a classification polarimetric method based on the support vector machine (SVM) which uses full- and the compact-pol modes. We present a study of the polarimetric information content derived from the decomposition for the CL-mode using Stokes parameter data products and from Freeman-Durden-decomposition derived from the full-pol imaging mode. We compare SVM classification both among the partial polarimetric datasets and against the full quad-pol dataset. We illustrate our results by using the polarimetric SAR images of Algiers city in Algeria acquired by the RadarSAT2 (FQ19) in C-band.
PubDate: 2013-12-14

• On Compromise Mixed Allocation in Multivariate Stratified Sampling with
Random Parameters
• Abstract: Abstract For estimating the population mean Clark and Steel (Stat. 49, 1970–207 2000) worked out the optimum allocation of sample sizes to strata and stages with simple additional constraints to use different type of allocations in different strata. Ahsan et al. (Aligarh J. Statist. 25, 87–97 2005) used the same idea to work out optimum allocation in univariate stratified sampling and called it a ‘Mixed Allocation’. Later on Varshney and Ahsan (J. Indian Soc. Agr. Stat. 65(3), 291–296, 2011) extended this work for multivariate stratified sampling and called it a compromise mixed allocation. This article presents a more realistic approach to the compromise mixed allocation by formulating the problem as a Stochastic Nonlinear Programming Problem in which the stratum-wise measurement costs and the sample stratum standard deviations are independent random variables with known probability distributions. The application of this approach is exhibited through a numerical example with normal distributions of the random parameters. The proposed compromise mixed allocation is compared with some other well known compromise allocations available in multivariate stratified sampling literature. It is found that the author’s proposed compromise mixed allocation is the most efficient allocation among the discussed allocations. A simulation study is also carried out to support the claim made by the authors on the basis of the results of the numerical example.
PubDate: 2013-12-03

• Reconstructing Convex Matrices by Integer Programming Approaches
• Abstract: Abstract We consider the problem of reconstructing two-dimensional convex binary matrices from their row and column sums with adjacent ones. Instead of requiring the ones to occur consecutively in each row and column, we maximize the number of adjacent ones. We reformulate the problem by using integer programming and we develop approximate solutions based on linearization and convexification techniques.
PubDate: 2013-12-01

• Generalized Univex Functions in Nonsmooth Multiobjective Optimization
• Abstract: Abstract In this paper, we have considered a nonsmooth multiobjective optimization problem where the objective and constraint functions involved are directionally differentiable. A new class of generalized functions (d − ρ − η − θ)-type I univex is introduced which generalizes many earlier classes cited in literature. Based upon these generalized functions, we have derived weak, strong, converse and strict converse duality theorems for mixed type multiobjective dual program in order to relate the efficient and weak efficient solutions of primal and dual problem.
PubDate: 2013-12-01

• Minimum Cost Compromise Mixed Allocation
• Abstract: Abstract When more than one (say p) characteristics in multivariate stratified population are defined on each unit of the population, the individual optimum allocations may differ widely and can not be used practically. Moreover, there may be a situation such that no standard allocation is advisable to all the strata, for one reason or another. In such a situation, Clark and Steel (J R Stat Soc, Ser D Stat 49(2):197–207, 2000) suggested that different allocations may be used for different groups of strata having some common characteristics for double sampling in stratification. Later on, Ahsan et al. (Aligarh J Stat 25:87–97, 2005) used the same concept in univariate stratified sampling. They minimized the variance of the stratified sample mean for a fixed cost to obtain an allocation and called this allocation “mixed allocation”. In the present paper, a “compromise mixed allocation” is worked out for the fixed precisions of the estimates of the p-population means of a multivariate stratified population. A numerical example is also presented.
PubDate: 2013-12-01

• Generalized Algorithm for Restricted Weak Composition Generation
• Abstract: Abstract This paper presents a new algorithm that arrives at a generalized solution for the generation of restricted weak compositions of n-parts. In particular, this generalized algorithm covers many commonly sought compositions such as bounded compositions, restricted compositions, weak compositions, and restricted part compositions. Introduced is an algorithm for generating generalized types of restricted weak compositions called first-order, and second-order restricted weak compositions.
PubDate: 2013-12-01

• Optimum Allocation in Two-Stage Stratified Randomized Response Model
• Abstract: Abstract In the present paper a two-stage stratified Warner’s randomized response model is used to determine the optimum allocation in the presence of non-response. The problem is formulated as a Nonlinear Programming Problem. A complete method of solution of the formulated problem is proposed. Two numerical examples are worked out to illustrate the computational details of the proposed method.
PubDate: 2013-12-01

• Designing WDM Optical Networks Using Branch-and-Price
• Abstract: Abstract In this paper, we present an exact solution procedure for the design of two-layer wavelength division multiplexing (WDM) optical networks with wavelength changers and bifurcated flows. This design problem closely resembles the traditional multicommodity flow problem, except that in the case of WDM optical networks, we are concerned with the routing of multiple commodities in two network layers. Consequently, the corresponding optimization models have to deal with two types of multicommodity variables defined for each of the network layers. The proposed procedure represents one of the first branch-and-price algorithms for a general WDM optical network setting with no assumptions on the number of logical links that can be established between nodes in the network. We apply our procedure in a computational study with four different network configurations. Our results show that for the three tested network configurations our branch-and-price algorithm provides solutions that are on average less than 5 % from optimality. We also provide a comparison of our branch-and-price algorithm with two simple variants of the upper bounding heuristic procedure HLDA that is commonly used for WDM optical network design.
PubDate: 2013-12-01

• A PTAS for a Particular Case of the Two-machine Flow Shop with Limited
Machine Availability
• Abstract: Abstract In this paper we develop a polynomial-time approximation scheme for a particular case of the two-machine flow shop scheduling problem with several availability constraints on the second machine under the resumable scenario.
PubDate: 2013-11-16

• Goal Directed Programming for Determining Process Efficiency Using Data
Envelopment Analysis
• Abstract: Abstract There are numerous measurement methods for process performance control. One of which, widely used in quality control programs, is process capability (C p ) index. The advantage of this index is due to the high amount of information extracted from it. Since C p is independent from a particular measurement unit it can be used to compare several quite different processes. While the relative efficiency of the process performance based on the C p for a period is satisfying, the process may lose efficiency in the next period for variety of reasons and could not keep up with the standard limits. The objective of this paper is to develop a new approach for measuring the relative efficiency of peer decision making units (DMUs) based upon process capability indices. A case study demonstrates the applicability of the proposed approach.
PubDate: 2013-11-07

• Mixed Type Duality in Multiobjective Fractional Programming Under
Generalized ρ-univex Function
• Abstract: Abstract In this paper, three approaches given by Dinklebaeh (Manag Sci 13(7):492–498, 1967) and Jagannathan (Z Oper Res 17:618–630, 1968) for both primal and mixed type dual of a non differentiable multiobjective fractional programming problem in which the numerator of objective function contains square root of positive semi definite quadratic form are introduced. Also, the necessary and sufficient conditions of efficient solution for fractional programming are established and a parameterizations technique is used to established duality results under generalized ρ-univexity assumption.
PubDate: 2013-10-24

• An Optimal Chance Constraint Multivariate Stratified Sampling Design Using
Auxiliary Information
• Abstract: Abstract When we are dealing with multivariate problem then we need an allocation which is optimal for all the characteristics in some sense because the individual optimum allocations usually differ widely unless the characteristics are highly correlated. So an allocation called “Compromise allocation” is to be worked out suggested by Cochran. When auxiliary information is also available, it is customary to use it to increase the precision of the estimates. Moreover, for practical implementation of an allocation, we need integer values of the sample sizes. In the present paper the problem is to determine the integer optimum compromise allocation when the population means of various characteristics are of interest and auxiliary information is available for the separate and combined ratio and regression estimates. This paper considers the optimum compromise allocation in multivariate stratified sampling with non-linear objective function and probabilistic non-linear cost constraint. The probabilistic non-linear cost constraint is converted into equivalent deterministic one by using Chance Constrained programming. The formulated multi-objective nonlinear programming problem is solved by Fuzzy Goal programming approach and Chebyshev approximation. Numerical illustration is also given to show the practical utility of the approaches.
PubDate: 2013-10-24

• A Generic Interior-point Algorithm for Monotone Symmetric Cone Linear
Complementarity Problems Based on a New Kernel Function
• Abstract: Abstract Kernel functions play an important role in defining new search directions for interior-point algorithms for solving monotone linear complementarity problems. In this paper we present a new kernel function which yields the complexity bounds ${\mathcal O}(\sqrt{r}\log r\log\frac{r}{\epsilon})$ and ${\mathcal O}(\sqrt{r}\log\frac{r}{\epsilon})$ for large-and small-update methods, respectively, which are currently the best known bounds for such methods.
PubDate: 2013-10-22

• Web Page Textual Color Contrast Compensation for CVD Users Using
Optimization Methods
• Abstract: Abstract With this paper, we propose two methods for color contrast compensation of the textual information contained in a web page using numerical optimization. The optimization process can be reduced to the minimization of a single objective function which aims to achieve an on-the-fly compensation inducing a small amount of change in the original colors. Mass-spring system based optimization and CMA-ES metaheuristics are compared with the problem in order to assess their efficiency for compensating the loss. Experiments conducted on real and artificial datasets, prove the methods efficiency even with a small number of evaluations. Also, the methods behaviour is bound to the amount of compensation needed.
PubDate: 2013-10-19

• Optimum Allocation in Multivariate Stratified Random Sampling: A Modified
Prékopa’s Approach
• Abstract: Abstract Considering the possible correlation between the characteristics (variables) in multivariate stratified random sampling, a modified Prékopa’s approach is suggested for the problem of optimum allocation in multivariate stratified random sampling. An example is solved by applying the proposed methodology.
PubDate: 2013-09-21

• An Iterated Local Search for the Budget Constrained Generalized Maximal
Covering Location Problem
• Abstract: Abstract Capacitated covering models aim at covering the maximum amount of customers’ demand using a set of capacitated facilities. Based on the assumptions made in such models, there is a unique scenario to open a facility in which each facility has a pre-specified capacity and an operating budget. In this paper, we propose a generalization of the maximal covering location problem, in which facilities have different scenarios for being constructed. Essentially, based on the budget invested to construct a given facility, it can provide different service levels to the surrounded customers. Having a limited budget to open the facilities, the goal is locating a subset of facilities with the optimal opening scenario, in order to maximize the total covered demand and subject to the service level constraint. Integer linear programming formulations are proposed and tested using ILOG CPLEX. An iterated local search algorithm is also developed to solve the introduced problem.
PubDate: 2013-09-13

• A Recursive Algorithm for State Dependent        class="a-plus-plus">GI/       class="a-plus-plus">M/1/       class="a-plus-plus">N
Queue with Bernoulli-Schedule Vacation
• Abstract: Abstract In this paper, we study a renewal input working vacations queue with state dependent services and Bernoulli-schedule vacations. The model is analyzed with single and multiple working vacations. The server goes for exponential working vacation whenever the queue is empty and the vacation rate is state dependent. At the instant of a service completion, the vacation is interrupted and the server resumes a regular busy period with probability 1 − q (if there are customers in the queue), or continues the vacation with probability q (0 ≤ q ≤ 1). We provide a recursive algorithm using the supplementary variable technique to numerically compute the stationary queue length distribution of the system. Finally, using some numerical results, we present the parameter effect on the various performance measures.
PubDate: 2013-09-11

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