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The Systems Optimization Learning and Renewable Energy (SOLAR) lab supports undergraduate and graduate research in the fields of Operations Research, Renewable Energy Planning and Parallel Computing. Students in the SOLAR lab research on practical problems such as finding the optimal deployment of wind and solar powered systems, cybersecurity in cyber physical systems and facility layout. The students also engage on research in the areas of logistics/supply chain, scheduling, vehicle routing and data analytics.

More than 15 students have worked in the SOLAR lab and their works have been presented in national and international conferences such as Institute for the Operations Research and Management Science (INFORMS), Institute of Industrial and Systems Engineering (IISE), Super Computing (SC) - The International Conference for High Performance Computing, Networking, Storage, and Analysis, Practice & Experience in Advanced Research Computing (PEARC), IEEE International Conference on Industrial Informatics (INDIN), IEEE Conference on Communications and Network Security (CNS), Extreme Science and Engineering Discovery Environment (XSEDE), Decision Sciences Institute (DSI) and Women in Engineering (WE) local conference from the Society of Women Engineers. Students have also presented at Texas State University internal conferences such as Women in Science and Engineering (WISE) and the International Graduate Research Conference.

The presentation and poster “Stochastic Models for Planning Distributed Wind Generation based on Data Analytics” done by graduate student Temitope Runsewe at the 2019 WE local Conference Collegiate competition in Baltimore won the 3rd place. The paper “Facility Layout at McNeil Warehouse Goodwill Industries” by Dr. Clara Novoa and undergraduate student Nhi Mai won the Honorable Mention (2nd place) in the Decision Sciences Institute Annual Meeting Best Application Paper Award competition in Fall 2012.

Equipment available in the SOLAR lab includes:



  • 1 Dell Optiplex 7010 desktop (3.4 GHZ Intel Core i5 3570 processor, 16 GB RAM, 460 GB Hard Drive) with one 24” wide screen monitor and running Windows 10 (64 Bit)
  • 2 Dell Optiplex 990 desktops (3.4 GHZ Intel Core i7 2600 processor, 16 GB RAM, 500GB Hard Drive) with two 30” wide screen monitors and running Windows 10 (64 Bit). One of them can also run CentOS though VirtualBox
  • 2 Dell OptiPlex 5040 desktops (3.2 GHZ Intel Core i5 6500 processor,16 GB RAM, 500 GB Hard Drive) with two 30" wide screen monitors and running Windows 10 (64 bit)


  • 1 HP Color Laserjet Printer
  • 2 Brother Color Laserjet Printers HL-3170CDW


General use software:

  • 5 Microsoft Office Enterprise (Includes Microsoft Visio and Microsoft Project)

Statistical software:

  • 4 Minitab
  • 4 SPSS

Mathematical optimization software:

  • 1 Knitro form Artelys
  • 4 AMPL with Knitro solver for non-linear programming
  • 1 Analytic Solver Platform
  • 2 GAMS
  • 4 IBM CPLEX optimization studio
  • 1 SYMPHONY and other open source optimization software Through VirtualBox and CentOS)
  • 4 Xpress
  • 4 Mathematica
  • 5 Matlab
  • 4 Mathcad Prime

Time study, assembly line balancing, and other miscellaneous IE software:

  • 1 TORA
  • 1 WinQSB
  • 1 Design tools
  • 4 Proplanner (it includes the modules ProTimeEstimation, ProBalance and the Autocad plugins: Workplace Planner and FlowPlanner)
  • 4 AutoCAD
  • 1 Paul Jensen Add-in
  • 1 HumanCAD
  • 1 Solidworks
  • 1 Work Study +


  • 4 Arena

Tools for connecting to clusters and remote servers:

  • 1 Xming
  • 4 Putty
  • 4 Filezilla
  • 1 SSH Secure file transfer and secure shell client

Tools for emulation a LINUX operating system

  • 3 Virtual Box
  • 1 CentOS

C/C++ Integrated Development Environment:

  • 3 Eclipse IDE for C/C++ and Java Programmers
  • 4 Microsoft Visual Studio Community
  • 1 Anaconda project
  • 1 Code::Blocks

Clusters and Servers Accessible by Remote Connection from the SOLAR lab:

  1. Leap - High Performance Computing Cluster - Texas state University
    It is a cluster managed by the Division of Information Technology (DOIT). The complete capabilities of the cluster are available at

  2. Capi - Computer Science Department Texas State University
    CAPI is a large memory machine. CAPI (Coherent Accelerator Processor Interface) was donated to the Texas State University Computer Science Department by IBM. CAPI runs under CentOS. It has 160 CPU’s, min speed 2.061 Ghz and max speed 3.690 Ghz, and 16GB memory. CAPI has an additional functionality for PCIe slots on CAPI enabled systems. It uses 16 PCIe slots and is layered on top of PCIe Gen 3. CAPI port is determined by the underlying PCIe 3.0 x16 technology, peaking at ca 16 GB/s, bidirectional.PCI Express 3.0's 8 GT/s bit rate effectively delivers 985 MB/s per lane, nearly doubling the lane bandwidth relative to PCI Express 2.0. 

  3.  Knuth computer - Computer Science Department Texas State University
    A six-core Intel processor based on the Sandybridge architecture. The server is equipped with a Tesla K20c NVIDIA GPU. This GPU also has 2496 cores grouped into 13 stream multiprocessors (SM's). The amount of shared memory available per block is 48K. On this platform, CPU code compiles with GCC Version 4.6.3 and CUDA code compiles with nvcc version 5.5. The server runs Ubuntu 12.04 as its operating system.

  4. Maverick 2 Cluster - Texas Advanced Computing Center (TACC) University of Texas at Austin – Pickle Research Center
    More information at

  5. Stampede 2 Cluster - Texas Advanced Computing Center (TACC) University of Texas at Austin – Pickle Research Center
    More information at

SOLAR lab Faculty:

Clara Novoa, Associate Professor at the Ingram School of Engineering Industrial Engineering Program. Her research areas are operations research (OR) and the use of high-performance computing for solving large-scale OR problems

SOLAR Lab Students Involved:

Industrial Engineering Graduate Students:

  • Divya Zala (Fall'18 - Present)
  • Temitope Runsewe (Spring 18 - Present)
  • Khan Siddique, Industrial Engineering (Spring 17 - Fall 17)
  • Gowtham Balachandran, Industrial Engineering (Spring 16 - Spring 18)

Computer Science Graduate Students:

  • Chandra Kolla, Graduate Student Computer Science Department (Fall 14 - Fall 15)
  • Abhilash Chaparala, Graduate Student Computer Science Department (Summer 13 - Summer 14)
  • Sujeeth Pasham, Graduate Student Computer Science Department (Spring 12 - Spring 13)

Engineering Technology Graduate Students:

  • Fei Sun, Graduate Student Engineering Technology Department (Spring 13 - Spring 15)
  • Hayden Beauchamp, Graduate Student Engineering Technology Department (Spring 12 - Spring 13)

Industrial Engineering Undergraduate Students:

  • Jordan Givens (Fall 17 - Spring 18)
  • Karina Yanes Portillo (Fall 14 – Spring 17)
  • Chandler Franklin (Fall 14 – Spring 15)
  • Cameron Paiga (Fall 13 – Spring 14)
  • Nhi Mai (Fall 11 – Spring 13)
  • Molly McDaniel (Fall 11 – Spring 12)
  • Suleima Alkusari (Fall 10 – Spring 11)

Computer Science Undergraduate Students:

  • Abigail Barron (Spring 16 - Fall 17)