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Sensitivity analysis is one of the most interesting and preoccupying areas in optimization. Many attempts are made to investigate the problem’s behavior when the input data changes.

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Sensitivity analysis in linear and convex quadratic optimization: Invariant active constraint set and invariant set intervals

Published in INFOR: Information Systems and Operational Research, 2006

Support set invariancy sensitivity analysis is concerned with the finding the range of parameter variation so thai the perturbed problem has still an optimal solution with the same support set that Ihe given optimal solution of the unperturbed problem has.

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Generalized support set invariancy sensitivity analysis in linear optimization

Published in Journal of Industrial & Management Optimization, 2006

Support set invariancy sensitivity analysis deals with finding the range of the parameter variation where there are optimal solutions with the same positive variables for all parameter values throughout this range.

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Support set invariancy sensitivity analysis in bi-parametric linear optimization

Published in ADVANCED MODELING and OPTIMIZATION, 2007

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Active Constraint Set Invariancy Sensitivity Analysis in Linear Optimization

Published in Journal of optimization theory and applications, 2007

Active constraint set invariancy sensitivity analysis is concerned with finding the range of parameter variation so that the perturbed problem has still an optimal solution with the same support set that the given optimal solution of the unperturbed problem has.

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Sensitivity analysis in convex quadratic optimization: simultaneous perturbation of the objective and right-hand-side vectors

Published in Algorithmic Operations Research, 2007

In this paper we study the behavior of Convex Quadratic Optimization problems when variation occurs simultaneously in the right-hand side vector of the constraints and in the coefficient vector of the linear term in the objective function.

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Support set expansion sensitivity analysis in convex quadratic optimization

Published in Optimization Methods and Software, 2007

In support set expansion sensitivity analysis, one concerns to find the range of parameter variation where the perturbed problem has an optimal solution with the support set that includes the support set of the given optimal solution of the unperturbed problem.

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Bi-parametric convex quadratic optimization

Published in Optimization Methods & Software, 2010

In this paper, we consider the convex quadratic optimization problem with simultaneous perturbation in the right-hand side of the constraints and the linear term of the objective function with different parameters.

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Interpretation of Different Approaches to Sensitivity Analysis in Cash Flow Problem

Published in MATEMATIKA: Malaysian Journal of Industrial and Applied Mathematics, 2013

Cash is the driving power of all business and cash-flow statement is one of the major issues of institutions, especially in crisis.

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A General Modeling Framework for the Long-Term Scheduling of Multiproduct Pipelines with Delivery Constraints

Published in Industrial & Engineering Chemistry Research, 2014

Common carrier pipelines are one of the most economic modes for transportation of petroleum refined products over land, especially when huge amounts of these products have to be pumped toward long-distance terminals.

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Matrix perturbation and optimal partition invariancy in linear optimization

Published in Asia-Pacific Journal of Operational Research, 2015

Understanding the effect of variation of the coefficient matrix in linear optimization problem on the optimal solution and the optimal value function has its own importance in practice.

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On the scheduling of real world multiproduct pipelines with simultaneous delivery

Published in Optimization and engineering, 2015

Common carrier pipelines are the best suited mode for transporting large volumes of petroleum products from production areas to long-distance terminals.

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A novel monolithic MILP framework for lot-sizing and scheduling of multiproduct treelike pipeline networks

Published in Industrial & Engineering Chemistry Research, 2015

Detailed scheduling of long-distance multiproduct pipelines has received growing attention in the past few years. It helps the planner to reduce the number of pump and segment switches between active and idle conditions to obtain savings on pump operating and maintenance costs.

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A Novel Metaheuristics for Optimization Inspired by Mother-Infant Communication in Animal Colonies

Published in Journal of Hyperstructures, 2016

Mother infant vocalization from distance in some animal spceies as bats, gulls and penguins is a basic tool to find the other’s location.

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Controlling Floods by Optimization Methods

Published in Water Resources Management, 2016

Floods as natural phenomena exist and will continue to occur. No manmade project can stop a flood from happening, but there are several effective methods to reduce its risk, aftermath and consequences.

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Short-term scheduling of multiple source pipelines with simultaneous injections and deliveries

Published in Computers & Operations Research, 2016

This paper addresses the optimal scheduling of straight pipelines featuring multiple intermediate nodes acting as dual-purpose stations, with a continuous-time Mixed-Integer Linear Programming formulation partly derived from Generalized Disjunctive Programming.

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PROPOSING TWO LINEAR PROGRAMMING MODELS IN UNCERTAIN ENVIRONMENT

Published in Journal of Operational Research in Its Applications, 2016

Uncertainty is one of the intrinsic characteristics of natural phenomena, and optimization is not an exception here. Parameters in an optimization problem may not be known exactly or may experience variation after finding an optimal solution.

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Semidefinite relaxation for dominating set

Published in Iranian Journal of Operations Research, 2017

It is a well-known fact that finding a minimum dominating set and consequently finding the domination number of a general graph is an NP-complete problem.

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Solving multi-period interdiction via generalized Bender’s decomposition

Published in Acta Mathematicae Applicatae Sinica, English Series, 2017

This paper considers a novel formulation of the multi-period network interdiction problem.

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Grouping Objects to Homogeneous Classes Satisfying Requisite Mass

Published in Journal of Artificial Intelligence & Data Mining (JAIDM), 2018

Grouping datasets plays an important role in many scientific researches. Depending on data features and applications, different constrains are imposed on groups, while having groups with similar members is always a main criterion.

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DETERMINING OPTIMUM PREMIUMS FOR HOMOGENOUS RISK GROUPS: A CASE STUDY

Published in JOURNAL OF OPERATIONAL RESEARCH AND ITS APPLICATIONS (JOURNAL OF APPLIED MATHEMATICS), 2018

Fair premium pricing is one of the main concerns in insurance texts. In this paper, by considering the demand functions, costs of claims and values at risks in homogenous risk groups of cargo insurance policies, we determine the optimum premiums.

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One-Stage Uncertain Linear optimization

Published in Journal of Hyperstructures, 2018

Uncertainty is one of the intrinsic features of natural phenomenon and optimization is not an exception. Parameters in an optimization problem may be inaccurately presented, or due to variation after solving the problem, the current optimal solution may not be optimal or feasible for the new data. One of the approaches towards the uncertainty is the uncertainty theory initiated by Liu in 2007 and completed in 2011.

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Uncertain weighted dominating set: a prototype application on natural disaster relief management

Published in Soft Computing, 2018

Indeterminacy is an intrinsic characteristics of real-world data. Where they originate from credible experiments, probability theory is a robust tool to manipulate this type of indeterminacy.

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Dynamic network interdiction problem with uncertain data

Published in International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 2018

This paper proposes an uncertain multi-period bi-level network interdiction problem with uncertain arc capacities. It is proved that there exists an equivalence relationship between uncertain multi-period network interdiction problem and the obtained deterministic correspondent.

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A novel DEA model based on uncertainty theory

Published in Annals of Operations Research, 2018

In deterministic DEA models, precise values are assigned to input and output data while they are intrinsically subjected to some degree of uncertainty

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Uncertain Network Interdiction Problem

Published in Journal of Uncertain Systems, 2018

Indeterminacy is an intrinsic characteristic of a decision making process. Sometimes there are no samples, and historical data are not enough for estimating an appropriate probability distribution for an indeterminate variable.

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Application of Dempster-Shafer theory in combining the experts’ opinions in DEA

Published in Journal of the Operational Research Society, 2019

In data envelopment analysis models, values of inputs, outputs and their slack weights are usually based on the domain experts’ opinions.

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Roman domination problem with uncertain positioning and deployment costs

Published in Soft Computing, 2020

In a connected simple graph, the weighted Roman domination problem is considered at which the cost of positioning at each vertex is imposed in addition to the costs of potential deployments from a vertex to some of its neighboring vertices.

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Identification of minimum set of master regulatory genes in gene regulatory networks

Published in IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2020

Identification of master regulatory genes is one of the primary challenges in systems biology.

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Induced optimal partition invariancy in linear optimization: constraints perturbation

Published in arXiv preprint arXiv:2008.02305, 2020

In this paper, we study uni-parametric linear optimization problems, in which simultaneously the right-hand-side and the left-hand-side of constraints are linearly perturbed with identical parameter

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Advances in induced optimal partition invariancy analysis in uni-parametric linear optimization

Published in Journal of Mathematical Modeling, 2020

In this study, we consider a family of uni-parametric linear optimization problems that the objective function, the right, and the left hand side of constraints are linearly perturbed with an identical parameter.

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Network data envelopment analysis in uncertain environment

Published in Computers & Industrial Engineering, 2020

In the Network data envelopment analysis, in addition to external inputs and outputs of a decision-making unit, interactions between internal subprocesses are also respected.

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