Automating the search for solutions to engineering problems can take either of two broad approaches: design exploration or design optimization. Practitioners making technology choices need to understand which tools do one, which do the other, and which approach best fits their needs. A global roster of commercially available design exploration and optimization software appears at the end of this post.
“Design Exploration is a particular way of arriving at an optimal design solution. To be formal, design exploration is the human-driven, often computer-assisted, divergent/convergent process used to evolve and investigate multidisciplinary design space with the intent of design discovery and to inform decision making throughout the design process.
“The essential difference between design optimization and design exploration is the method for characterizing the outcome. Design optimization strategies have two distinct parts; formulate and converge. Here it is assumed that the problem can be formulated before the search and convergence begins. Design exploration strategies, on the other hand, are based on the belief that the problem formulation evolves during the process of searching and converging, thus ultimately leading to a more informed optimal solution. In this way, design exploration is both divergent and convergent.”
What does this mean for how the problem is formulated and solved?
“Design Optimization depends on a well-posed optimization problem formulation, which generally includes (i) a well-defined objective function, (ii) inequality and equality constraints, and (iii) the expression of stakeholder preference, all of which are likely to be multidisciplinary in nature. In an arguably real way, such a problem formulation predefines the optimum solution, thereby allowing the mathematical rigor of the optimization to lead to the optimum design by an iterative, computational search.
“Design Exploration, on the other hand, assumes that the optimal design is initially unknown and initially uncharacterizable. The process of design exploration discovers design conditions and little by little (often through some form of experimentation) characterizes what an optimal design looks like. Once this is known, the final solution can then be found through a convergent design optimization algorithm.”
Most CAE vendors today offer a greater or lesser degree of optimization capability as part of their mainstream product lines. Through strategic acquisitions and development, some now boast notably broad and deep offerings. At the same time, some of the best-regarded tools continue to come from smaller vendors focused exclusively on optimization.
While not as many companies offer design exploration software, top-tier products are available from several major CAE vendors as well as a healthy number of providers dedicated to this space. Engineering organizations contemplating a purchase should weigh their functional requirements against considerations of existing technology investments and vendor relationships.
Below are software products we’ve identified in each of these domains and classified according to our understanding of their primary function. It bears emphasizing that varying degrees of optimization capability are provided by most design exploration tool suites, even though we have not repeated the names of those products in the design optimization category following.
- Altair HyperStudy
- ANSYS DesignXplorer
- Autodesk Simulation CFD Design Study Environment, Autodesk Research Project Dreamcatcher
- CD-adapco STAR-CCM+ /Enabling Optimate
- CEI EnSight
- DATADVANCE MACROS, pSeven
- DecisionVis ExplorerDV
- Dynamic Design Solutions FEMtools Optimization
- Dynardo optiSLang
- eArtius Pareto Explorer
- ESTECO modeFRONTIER, SOMO
- Exa PowerFLOW Optimization Solution
- FRIENDSHIP SYSTEMS CAESES/FRIENDSHIP-Framework
- FunctionBay RecurDyn/AutoDesign
- iChrome Nexus
- InModelia Neuro Pex
- MSC Nastran Multi-run & Design Space Exploration
- Noesis Solutions Optimus
- OptiY GmbH OptiY
- Phoenix Integration ModelCenter
- PIDOTECH PIAnO
- PTC Creo BMX (Behavioral Modeling Extension)
- Red Cedar Technology HEEDS MDO
- Sandia National Laboratories Dakota
- Siemens PLM LMS Virtual.Lab Optimization
- Sigma Tech IOSO
- SIMULIA Isight
- Tecplot Chorus
- Vanderplaats Research & Development VisualDOC
- Altair OptiStruct, solidThinking Inspire
- ANSYS Adjoint Solver, Optimetrics
- Autodesk Simulation Mechanical Design Optimization
- CD-adapco STAR-CCM+ /Enabling Optimate+
- Cenaero Minamo
- Collier Research HyperSizer
- COMSOL Multiphysics Optimization Module
- Concepts NREC TurboOPT II
- divis ClearVu Global Optimizer
- ESI Group Virtual Performance Solution Optimization
- FEA-Opt SmartDO
- INTES PERMAS-OPT, PERMAS-TOPO
- LIONlab LIONsolver
- LSTC LS-OPT
- MSC Nastran Design Optimization
- NISA Software CSIL NISAOPT
- Optimal Solutions Sculptor
- Quint OPTISHAPE-TS
- RBF Morph
- Red Cedar Technology HEEDS NP
- Siemens PLM NX Nastran Optimization, Femap with NX Nastran Optimization
- SIMULIA Tosca
- SolidWorks Simulation Structural Optimization
- Vanderplaats Research & Development GENESIS, DOT, BIGDOT
- Virtualpyxis Virtual.PYXIS
- Within Technologies (an Autodesk company) Enhance
In future posts we’ll look at the role in design exploration and optimization of systems modeling technology from Comet Solutions, Maplesoft, The MathWorks, the Modelica Association, Modelon, the NPSS Consortium, OMG SysML, OpenModelica and Vitech, and 0D/1D simulation tools from AVL, Ricardo and others.