Research Interests:

Operations Research and Power System Optimization, Statistical Modeling and Applications in Industry, Data Mining and Process Improvement, Healthcare System Engineering, Mathematical and Probabilistic Modeling, Quality and Reliability Engineering, Simulation and Modeling, Six-Sigma and Lean Manufacturing, Supply Chain Management & Logistics, Inventory & Production Control


·        My PhD dissertation was concentrated on Optimization and Reliability analysis of Power Systems. The extensive development of power networks has increased the requirements for robust, reliable and secure monitoring and control techniques based on the concept of Wide Area Measurement System (WAMS). Phasor Measurement Units (PMUs) are key elements in WAMS based operations of power systems. Most existing algorithms consider the problem of optimal PMU placement where the main objective is to ensure observability. They consider cost and observability of buses ignoring the reliability aspect of both WAMS and PMUs. Given the twin and conflicting objectives of cost and reliability, this dissertation aims to model and solve a multi-objective optimization formulation that maintains full system observability with minimum cost while exceeding a pre-specified level of reliability of observability. No unique solution exists for these conflicting objectives, hence the model finds the best tradeoffs. In fact the reliability-based PMU placement model is Non-deterministic Polynomial time hard (NP-hard), therefore the mathematical model can only address small problems. The proposed research includes two tasks: (a) modeling and solving the multi-objective PMU placement model for IEEE standard test systems, and (b) developing heuristic algorithms to increase the scalability of the model and solve large size problems.

·        My research study also concentrated on three VA Funded Research and a NSF Funded Research.

·        VA Funded Research - Care Integration Optimization. The overarching goal for this project is to develop and test an optimization model using linear programming to maximize efficiency and minimize cost for the integrated care program at the NM VA HCS. The model focuses on minimizing travel distances for veterans, optimizing access to veterans via CBOC or tertiary care for specialty services, fee-for-care, or even mobile clinics if feasible while reducing travel times, maximizing the use of tele-medicine and its availability, optimizing patient driven care, personalized and proactive care, and striving to minimize cost to both VA and the veterans. This model mainly focuses on primary care access and service for veterans through a CBOC in the respective community or nearby communities and availability of tertiary care and access to it or the use of tele-medicine. The team utilized simulation to test the model outcome and results. Arena used for simulation purposes.

·        VA Funded Research - Value Analysis of Clinic Visits. The purpose of this project is to perform a value analysis in order to identify Value Added and Non-Value Added activities in clinic visit operation at VA. The Value Added activities are to reduce waste and the Non-Value Added activities are of two types. Some are “Necessary” which must be stream lined and others are “Unnecessary” which must be eliminated.

·        VA Funded Research - Implementing Andon in Healthcare Delivery. We propose to develop an Andon system that could overcome the socio-technical barriers of incident reporting by using such technology in healthcare and would also pass the litmus test by staying functional and usable years after implementation.   The OR Department of New Mexico VA served as the pilot site for this project.

·        NSF Funded Research - Data-driven Support for the Smart Farm. We developed an economic model of Sugar-beet growing, transportation, and processing in the Red River Valley to incorporate changes in critical attributes directly as a result of forecast model(s) using remote senor data (NDVI) and in-situ sensor data (plant height), etc.  A methodology for the use of a baseline data for production costs of Sugarbeet farms and Sugarbeet processing costs at the factory level along with criteria that could be used as means of measuring benefits realized by the partners/growers is developed.

·        My MS thesis was on Warranty modeling using certain stochastic tools. The thesis discusses certain optimality issues regarding product pricing and warranty periods under various objective functions. Warranty contracts are an integral part of product sales and play a crucial role in the manufacturer’s profit and customer satisfaction. With the boom in the consumer goods market, there is an ever-growing need for extended warranty policies. This thesis develops and analyses extended warranty models with several innovative features. We consider a product which is subject to two kinds of failures, major and minor, requiring replacement and minimal repair respectively. Apart from the base warranty the consumer is offered several extended warranty policies to choose from. The present work obtains the long run average cost per unit per unit time for the various policies explicitly and discusses several optimality issues. We further introduce a displaced log linear demand function using which the total profit of the manufacturer is obtained. This objective function enables us to obtain the optimal warranty period and sales price of the product and to choose the best policy. Customer satisfaction has a major impact on sales in several ways which has serious cost implications for the manufacturer. We have modeled probabilistically the customer satisfaction and have incorporated it into the manufacturer’s total profit function. This realistic objective function is optimized to determine several decision variables.


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