Talk:SORCER/Archive 3

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Reply to 74.192.84.101 re citation counts.

Hi 74,

There are a lot of article (and deleted articles) along the lines of SORCER, and if we followed the notability guidelines in WP:NSOFT all of them would be deleted: there just isn't coverage in popular magazines and books for these kinds of topics. If we went to the other extreme and allowed peer-reviewed publications to count equally with magazines and books, we'd be flooded with low-quality articles on topics where there are only a handful of (mostly-ignored) papers we can use as citations.

So somewhere between these two extremes is something sensible. My own rule of thumb is that if a paper describing a CompSci topic has 100+ citations, then I have no problem justifying an article: other people outside of that research group think the topic is important enough to cite. If I see lots of papers with <25 citations, that looks to me like a research group is cranking out papers, but the impact outside of the immediate group hasn't been sufficient to warrant an article. (Note that a highly-cited article that only mentions the topic does not establish notability.)

I assume you're aware of how to use google scholar to get citation counts; let me know if you're not.

Did that answer your questions? I'm happy to continue the conversation here or by email if you prefer. Garamond Lethet
c 23:54, 2 January 2014 (UTC)

Hadn't run across it before, but WP:NSOFT is a pretty reasonable essay, so although it doesn't trump WP:GNG, your point about pet projects that are WP:SPIP for some small research group is well-taken. For the benefit of myself, but more importantly, the others who may read later, here are the essentials as applied to the SORCER/exertions/etc topic. An ideal software article should include:
  1. A short overview. See "Talk:SORCER#paragraph one" rewrite attempt, above. SORCER is part grid-computing infrastructure, and part "other things", mainly used in the field of CAE/CAD/CAM for aerospace-engineers designing & simulating new vehicles/weapons/etc
  2. An assertion of notability. Nutshell: SORCER makes the aerospace weapon-systems design-process dramatically more speedy/flexible/radical, via software-only automated-design-optimization-for-hypersonic-flight plus real-world-final-capability-prediction-from-CAD-blueprints.
  3. ... Details: as of 2012, SORCER's grid-computing stuff permits automated non-linear analysis of aircraft-designs, while they are still virtual (i.e. in CAD virtual-blueprint form), and accomplishes this in the same timeframe that traditional linear efforts take; cite is DaytonThesis. (This means initial aerospace work can proceed without the need to physically prototype for wind-tunnel work, cutting out one-or-more loops from the incremental-design-process.)
  4. ... As of 2013, the USAF published some results on using SORCER to predict final manufacturing costs && final real-world offensive/defensive capabilities, again based purely on CAD-virtual-blueprints, no physical prototype required, no full-size physical testing of previous design-variants required; cite iosPress#1 conf-paper in print-proceedings. (This means that relatively radical designs can be virtually prototyped, at low cost, and then virtually "flown" in simulation, using SORCER to speed up both the design-work and the sim-work... end result is a ton of innovative pure-software designs can be jammed out in a relatively brief timespan, with predictions of final value/ROI directly useful to the top brass && civilian leadership that decides which advanced aerospace-systems get the funding.)
  5. ... Finally, although I don't understand Mandarin so I'm handicapped on summarizing the effort, there is a good sized R&D effort in China, which has been doing traffic-noise mapping since 2009 (around ten refereed academic papers), and there is now a 2012/2013/2014/2015 high-speed-rail effort funded by NSFC (not sure if any papers from this are non-classified).
  6. A software infobox with information on version number, developer, etc. This is tricksy, because SORCER has several independent forks (GE/Dassault/USAF/SorcerSoftOrg/Poland#1/Poland#2/PJIIT/Russian/Chinese ... that I know of!). Gerda_Arendt will be disappointed that the infobox is not likely to be very helpful to this article.  :-)   It makes sense to put the main open-source repo into the infobox, but I'm not sure if that is TTU, SorcerSoftOrg, or Poland#1 aka SorcerSoftCom-open-source-fork.
  7. An appropriate comparison/timeline of significant release versions. Yes, working on this, see my upmteen questions above.  :-)

I've collected some data from Google Scholar (see above 17:15, 3 January 2014 in the 'notability discussion' section and the 'neologism' and also perhaps at 17:33, 3 January 2014 section), and come to agree with Garamond that SORCER/FIPER is not expecially academically wikiNotable as computer science ... rather, it is academically wikiNotable as computer aided engineering, methinks. WP:NSOFT#Inclusion says we need:

  1. discussed in WP:RS as significant in its particular field (distributed collaborative computer aided engineering). Methinks we've got this, see notability-discussion above.
  2. subject of instruction at multiple schools; does not apply to software merely used in instruction. We have a bit of this ... Professor Sobolewski has taught SORCER at TTU, PJIIT, and in several other countries... there is a list of his visiting-professorships in his sorcersoft.org resume, which I copied at one point, I'll paste it when I find it again.
  3. multiple printed third-party manuals/tutorials/reviews. Nope! There is no such thing as SORCER For Dummies down at the local amazon store.  :-)
  4. published software that has been recognized (by reviewers) as having historical or technical significance by reliable sources. There are a couple lit-survey-papers, see details above, but SORCER is not reviewed in PC Magazine or anything like that.

Any one of the four is good enough. Also, WP:NSOFT says this: "It is not unreasonable to allow relatively informal sources for free and open source software, if significance can be shown." Since the spin-off during 2010, SORCER is officially open-source, and we have some evidence that the folks in Russia and China are using it... beyond what GoogleScholar shows. Additionally, we also have ongoing academic publications at conferences, and a new commercial entity. But methinks these latter two are not the story; the story is the CAE work done at government and university labs. 74.192.84.101 (talk) 17:52, 3 January 2014 (UTC)

Hi 74. There is a lot of "above" to see. Can you give me the pointers to the lit-review papers? Thanks! Garamond Lethet
c 20:48, 3 January 2014 (UTC)
Garamond, the green boxes at 17:15, 3 January 2014 and also perhaps at 17:33, 3 January 2014 should have what you need, use ctrl+f. There is compsci lit by Sobolewski and co-authors, but there is more significant breadth in the CAE lit (for aerospace-engineering and industrial-engineering folks rather than EECS folks). HTH. 74.192.84.101 (talk) 21:09, 3 January 2014 (UTC)
74, I'm sorry, I wasn't clear. Which one of these is the "lit survey paper"? Garamond Lethet
c 21:20, 3 January 2014 (UTC)
No, my apologies, totally my reading-comprehension failure, I thought you were asking for the list of papers, aka *my* personal "lit-research" via goog-skol. My brain autocorrected a typo you hadn't actually made.  :-)   As for your answer, mhhhhmmmm, maybe Pawelpacewicz will have a better chance at answering that more fully. The one *I* knew about (but see below for another I ran across a few hours ago) was a pair of U.Cranfield papers by Goteng et al from 2007, which is about the time SORCER was starting to publish heavily, and FIPER had just peaked and newly-published papers on FIPER were going downhill. This particular lit-review paper is not cited by others, according to GoogleScholar, but the folks involved are independent academics from another subdiscipline, and the publisher is impeccable, which is why Beavercreekful brought it up. Evolutionary Computing within Grid Environment, Springer, 2007, presented(?) at [Advances in] Evolutionary Computing for System Design, published in Studies in Computational Intelligence Volume 66, isbn 978-3-540-72376-9, pages 229-248, which is 19 pages total, not sure how much ink SORCER got. Authors are Ashutosh Tiwari, Gokop Goteng, Rajkumar Roy.
  Couple years later, Goteng got their PhD at U.Cranfield, and did a more serious lit-review, with more pages[1] on FIPER-or-SORCER therein; the main TTU papers on exertion-oriented-programming and SORCER were both in 2007/2008, but methinks Goteng just talked about FIPER, because SORCER was still closed-source in 2009 (opened in 2010). Development of a Grid Service for Multi-objective Design Optimisation, Gokop Goteng PhD, "lit review & industry survey ... of grid services ... [including FIPER-or-SORCER]", 2009, School of Applied Sciences, Cranfield University. Now, although Goteng's PhD has also gotten no goog-skol-cites so far, the thesis-cmte of 2009, and the peer-reviewers-slash-editors of 2007, made both Goteng-papers into an in-depth independent Reliable Source, distinct from anybody connected with SORCER/FIPER, and therefore counting towards WP:GNG. That said....

That said, we can also look at the wider literature in that specific research-niche, and see that SORCER/FIPER did not become the rock-star of Multi-objective optimization within Evolutionary computing within Algorithms within Computer Science (plus application to economics and also financial markets). Yet, at least. SORCER is definitely known in the subfield, though mostly by aerospace-engineering folks, at present. FIPER is older and thus better-known, including by the "top" guy in the Multi-objective Optimization, based on google-scholar-raw-hit-counts at least.

analysis of the MOO literature, per goog-scholar, first line is search-term, number results are hits-with-cites

Multi-objective Optimisation "SORCER"

  1. Aeroelastic Optimization of a Two-Dimensional Flapping Mechanism DE Bryson, TA Weisshaar, RD Snyder… - … 국내연구성과| IP 제공정보 …, 2010 - arc.aiaa.org Cited by 2 2010 AIAA for CAE , not ACM/IEEE for EECS
  2. Efficient Supersonic Air Vehicle Preliminary Conceptual Multi-Disciplinary Design Optimization Results E Alyanak, R Kolonay, -, 2012 - arc.aiaa.org Cited by 2 2012 AIAA for CAE , not ACM/IEEE for EECS
  3. Standard Platform for Benchmarking Multidisciplinary Design Analysis and Optimization Architectures J Gray, KT Moore, TA Hearn, BA Naylor - AIAA journal, 2013 Cited by 1 2013 AIAA for CAE , not ACM/IEEE for EECS

Multi-objective Optimisation "FIPER" Multi-objective Optimisation "FIPER"

  1. Current trends in evolutionary multi-objective optimization K Deb - … Simulation and Multidisciplinary Design Optimization, 2007 - ijsmdo.org Cited by 33 2007 6 cites/yr for rockstar K.Deb
  2. MOB a European distributed multi-disciplinary design and optimisation project AJ Morris - Proceedings of the 9th AIAA/ISSMO Symposium on …, 2002 - arc.aiaa.org Cited by 28 2002 FIPER
  3. Design search and optimization in aerospace engineering AJ Keane, JP Scanlan - … Transactions of the Royal …, 2007 - rsta.royalsocietypublishing.org Cited by 11 2007
  4. Introduction to evolutionary multiobjective optimization K Deb - Multiobjective Optimization, 2008 - Springer Cited by 27 2008 5 cites/yr for rockstar K.Deb
  5. CAD based shape optimization for gas turbine component design D Brujic, M Ristic, M Mattone, P Maggiore… - … Optimization, 2010 - Springer Cited by 6 2010
  6. iSIGHT-FD, a tool for multi—objective Data Analysis A Van der Velden, B Wujek, P Koch - … 프로시딩즈| 기술보고서| 해외연구 …, 2008 - arc.aiaa.org Cited by 3 2008
  7. Multidisciplinary Design Optimization of Missile Based on FIPER Software T LI, L GU - Computer Simulation, 2009 - en.cnki.com.cn Cited by 1 2009
  8. Multidisciplinary optimization of naval ship design and mission effectiveness J Vianese - 2004 - DTIC Document Cited by 5 2004
  9. A hierarchical federated integration architecture for collaborative product development H Sun, W Fan, W Shen, T Xiao… Journal …, 2012 - Taylor & Francis Cited by 2 2012
  10. Knowledge Based Engineering (KBE) Past, present and Future A Prijic, C Chapman, P Burton - Beograd 2005 EAEC European Automotive Congress Cited by 2 2005
  11. Use of CAPE-OPEN Standard in US-UK Collaboration on Virtual Plant Simulation SE Zitney - AIChE 2007 Annual Meeting, 4th Annual US CAPE- …, 2007 - co-lan.org Cited by 2 2007
  12. Towards a standardized engineering framework for distributed, collaborative product realization HJ Choi, JH Panchal, JK Allen, Proceedings, 2003 gatech.edu Cited by 18 2003 FIPER
  13. PROGRESS REPORT ON NEW MODELLING TECHNIQUES D Brujic, M Ristic, M Mattone, P Maggiore… - 2005 - modefrontier.de Cited by 1 2005
  14. Ein Beitrag zur interdisziplinären Prozessintegration und automatischen Mehrzieloptimierung am Beispiel einer Verdichterrotorschaufel, D Otto - 2009 - opus.kobv.de Cited by 1 2009
  15. Developing a Design Space Model Using a Multidisciplinary Design Optimization Schema in a Product Lifecycle Management System… NL Fife - 2005 - Citeseer Cited by 3 2005
  16. Facilitating meta-design via separation of problem, product, and process information JH Panchal, MG Fernández… - 2005 ASME …, 2005 - westinghouse.marc.gatech.edu Cited by 6 2005
  17. Computational workflow management for conceptual design of complex systems: an air-vehicle design perspective LK Balachandran - 2007 - dspace.lib.cranfield.ac.uk Cited by 2 2007
  18. Addressing Geometry Needs of Systems Engineering with DaVinci Software G Roth, J Livingston, C Dailey, A Cline - 49th AIAA, 2011 - arc.aiaa.org Cited by 1 2011
  19. An adaptable service-based framework for distributed product realization JH Panchal, HJ Choi, JK Allen, D Rosen… - … Product Design and …, 2007 - Springer Cited by 5 2007
  20. Feasibility assessment in preliminary design using Pareto sets A Gurnani, S Ferguson… - ASME Design …, 2005 - does.eng.buffalo.edu Cited by 11 2005 Gurnani#1
  21. An Approach to Feasibility Assessment In Preliminary Design S Ferguson, A Gurnani, J Donndelinger… - ASME Design …, 2005 - atsv.psu.edu Cited by 5 2005 Gurnani#2
  22. Design and analysis of computer experiments in multidisciplinary design optimization: a review TW Simpson, V Toropov, V Balabanov…, 2008, aiaa.org Cited by 106 2008 21 cites/yr for this lit-review by AIAA ... gold? Could not find full paper online, paywall[2] shows only first page, U.Leuv(sp) used to have PDF but site was offline when I checked. Author emails listed, maybe one will help out?
  23. e-Design Systems BO Nnaji, Y Wang, KY Kim - The Handbook of Industrial and …, 2005 - 203.158.253.140 Cited by 2 2005
  24. Thermo-economic assessment of externally fired micro-gas turbine fired by natural gas and biomass AM Pantaleo, SM Camporeale, N Shah, 2013 - Elsevier Cited by 3 2013
  25. Towards a design support system for distributed product realization JH Panchal - 2003 - srl.gatech.edu Cited by 3 2003
  26. Cost-Effective Product Realization-Service-Oriented Architecture for Integrated Product Life-Cycle Management BO Nnaji, Y Wang, KY Kim - 7th IFAC, 2004 Cited by 8 2004
  27. Nesting automated design modules in an interconnected framework JM Young - 2005 - Citeseer Cited by 3 2005
  28. A design tool architecture for the rapid evaluation of product design tradeoffs in an Inernet-based system modeling environment JJA Wronski - 2005 - mit.edu Cited by 8 2005
  29. Multi-objective evolutionary optimization in time-changing environments I Hatzakis - 2007 - dspace.mit.edu Cited by 2 2007

Multi-objective Optimisation ("M. Sobolewski" OR "M Sobolewski" OR "Mike Sobolewski" OR "Michael Sobolewski" OR "Sobolewski, M" OR "Sobolewski, M" OR "Sobolewski, Mike" OR "Sobolewski, Michael")

  1. Transmission systems design--decisions, multi-criteria optimization in distributed environment J Pokojski, K Niedziółka - Proceedings, 2006 - dl.acm.org Cited by 3 2006
  2. Multi-objective Optimization Model and Algorithms for Partner Selection MM Hassan, EN Huh - Dynamic Cloud Collaboration Platform, 2013 - Springer Cited by 1 2013 Hassan#1
  3. Dynamic Cloud Collaboration Platform: A Market-oriented Approach MM Hassan, EN Huh - 2013 - books.google.com Cited by 1 2013 Hassan#2
  4. A constraint-based approach to feasibility assessment in preliminary design A Gurnani, S Ferguson, K Lewis, J Donndelinger - AI EDAM, 2006 - Cambridge Univ Press Cited by 17 2006 Gurnani#3 ... 2.4 cites/yr
  5. Multi-objective optimization of multicast overlays for collaborative applications K Rzadca, JTT Yong, A Datta - Computer Networks, 2010 - Elsevier Cited by 3 2010
  6. Product, process and methodology systematization to handle structural and computational complexity in product realization B Prasad, 2001 - Wiley Online Library Cited by 2 2001
  7. Recent advances in engineering design optimisation: Challenges and future trends R Roy, S Hinduja, R Teti - CIRP Annals-Mfg Technology, 2008 - Elsevier Cited by 75 2008 15 cites/yr[3] by R.Roy DeptMfg U.Cranfield, S.Hinduja AeroEng U.Manchester, R.Teti MatEng&ProductionEng U.Naples. See analysis in section green box, immediately below.
  8. A hierarchical decision model to select quality control strategies for a complex product Y Liu, KW Hipel, 2012 - ieeexplore.ieee.org Cited by 4 2012

Multi-objective Optimisation .... aka this particular sub-sub-field in general, only the top 20 hits-with-cites are shown

  1. Multi-objective optimization K Deb - Multi-objective optimization using evolutionary …, 2001 - netscale.cse.nd.edu Cited by 8354 2001 700 cites/yr for rockstar K.Deb
  2. Multi-objective optimization K Deb - Search Methodologies, 2005 - Springer Cited by 122 2005 15 cites/yr for rockstar K.Deb
  3. A fast elitist non-dominated sorting genetic algorithm for multi-objective optimization: NSGA-II K Deb, S Agrawal, A Pratap, 2000 - repository.ias.ac.in Cited by 2796 2000 200 cites/yr for rockstar K.Deb
  4. Survey of multi-objective optimization methods for engineering RT Marler, JS Arora - Structural and multidisciplinary optimization, 2004 - Springer Cited by 916 2004
  5. A Multi-Objective Algorithm based upon Particle Swarm Optimisation, an Efficient Data Structure and Turbulence. JE Fieldsend, EQ Uk, S Singh - 2002 - Citeseer Cited by 258 2002
  6. A critical survey of performance indices for multi-objective optimisation T Okabe, Y Jin, B Sendhoff, CEC'03, 2003 - ieeexplore.ieee.org Cited by 123 2003
  7. Multi-objective optimization using genetic algorithms: A tutorial A Konak, DW Coit, AE Smith - Reliability Engineering & System Safety, 2006 - Elsevier Cited by 778 2006
  8. Evolutionary multi-objective optimization: a historical view of the field CA Coello Coello - Computational Intelligence Mag, IEEE, 2006 - ieeexplore.ieee.org Cited by 477 2006
  9. Strategies for finding good local guides in multi-objective particle swarm optimization (MOPSO) S Mostaghim, J Teich - …, SIS'03., 2003 - ieeexplore.ieee.org Cited by 404 2003
  10. Multi-objective global optimization for hydrologic models PO Yapo, HV Gupta, S Sorooshian - Journal of hydrology, 1998 - Elsevier Cited by 570 1998 classic
  11. Multi‐objective combinatorial optimization problems: A survey EL Ulungu, J Teghem - Journal of Multi‐Criteria Decision …, 1994 - Wiley Online Library Cited by 333 1994 classic
  12. Scalable multi-objective optimization test problems K Deb, L Thiele, M Laumanns… - Proceedings of the …, 2002 - repository.ias.ac.in Cited by 554 2002 50 cites/yr for rockstar K.Deb
  13. Multi-class ROC analysis from a multi-objective optimisation perspective RM Everson, JE Fieldsend - Pattern Recognition Letters, 2006 - Elsevier Cited by 75 2006
  14. PDE: a Pareto-frontier differential evolution approach for multi-objective optimization problems HA Abbass, R Sarker, C Newton, 2001. Proc, ieeexplore.ieee.org Cited by 332 2001
  15. Genetic local search for multi-objective combinatorial optimization A Jaszkiewicz - European journal of operational research, 2002 - Elsevier Cited by 460 2002
  16. Fundamentals of computational swarm intelligence AP Engelbrecht - 2005 - lavoisier.fr Cited by 1168 2005
  17. Multi-objective optimisation using the bees algorithm DT Pham, A Ghanbarzadeh - Proceedings of IPROMS 2007 …, 2007 - people.stfx.ca Cited by 59 2007
  18. Multi-objective optimisation applied to industrial energy problems G Leyland - 2002 - lania.mx Cited by 99 2002
  19. An evolution strategy with probabilistic mutation for multi-objective optimisation S Huband, P Hingston, L While…, CEC'03. The …, 2003 - ieeexplore.ieee.org Cited by 57 2003
  20. Evolutionary algorithms for solving multi-objective problems CAC Coello, GB Lamont, DA Van Veldhuisen - 2007 - books.google.com Cited by 3709 2007

Deeper analysis of the 75-cites-total paper which mentioned both Sobolewski and Kolonay. It turns out to be a survey-paper on engineering design optimization, which is a superset of multi-objective optimization, which in turn is a superset of mechanical/industrial multi-objective optimization (where FIPER and SORCER fit into this picture). Recent advances in engineering design optimisation,[4] 2008, by R.Roy DeptMfg U.Cranfield, S.Hinduja AeroEng U.Manchester, R.Teti ProductionEng U.Naples. Stuff in the double-parens is my interpretation, take with a grain of salt.  :-)

an overview of the major research areas in engineering design optimization, especially the CAE stuff

Section 10. Future challenges in algorithmic engineering design optimisation. Considering the growth in publications using the algorithmic approach for EDO, this approach has the best potential to improve a design. Fig. 10 shows lack of popularity of algorithmic approach for mechanical systems design optimisation compared to non-mechanical systems. ((JPEG: papers published per year, 1997 through 2006, in the field of design-optimization-generally-aka-mostly-for-software-apps versus the subfield of design-optimization-for-mechanical-parts-aka-trains-planes-and-automobiles. 400/yr to 1100/yr strong growth for non-mechanical EDO, versus only 50/yr to 200/yr tepid growth for mechanical EDO... which is FIPER and SORCER's speciality.)) This section identifies the major challenges of algorithmic approaches for real life optimisation and then comments on the possible reasons for lack of interest in the mechanical systems design community. The major challenges are:

  1. 1. Real life features: .... ((MATH == applied math context versus theoretical computer science context ... elegant algorithms often have pathological corner cases in practice that make the airplane-design go awry))
  2. 2. Model development: .... ((CAD&CAE == fundamental features))
  3. 3. Designer confidence: .... ((EECS == GUI design + knowledge-based systems AI))
  4. 4. Design improvement process: .... ((MBA == management buy-in and process re-engineering and other people-problems))
  5. 5. ((CAD&CAE == applied grid computing)) Computational expense of design evaluation: One approach to deal with computationally expensive design evaluation models is to develop surrogate models to replace the expensive design models. Increasingly there is demand to work with more accurate models and find ways to deal with the computational costs. In line with this there is increasing interest to solve real life large-scale design optimisation problems. Recently, use of grid and distributed computing is beginning to address this issue for large-scale optimisation problems.[141,142] This is discussed in more detail in Section 11. ((typo in original... they said 12 but obviously meant 11.))
  6. 6. ((CAD&CAE == advanced statistical features)) Qualitative design space: .... ((this is what Kolonay and Sobolewski are working on nowadays... predicting vehicle-defensive-capabilities *directly* from the raw CAD model giving length/weight/etc physical-data))
  7. 7. ((CAD&CAE == advanced simulation-based features)) Integration with CAD and simulation: The bidirectional interface between feature-based parametric CAD models and optimisation/analysis models that ensure automatic bidirectional conversions do not exist at present. Several researchers have identified this deficiency.[143,144] Nosner noted[143] that after the shape or topology optimisation stage, the design engineer still has to interact with the results to ensure that features are integrated into the CAD model in an appropriate way. Researchers[143,145] have noticed that the lack of feature information prevents the application of meaningful engineering constraints. Addressing these needs requires high level geometric reasoning such as feature technology/recognition to be more integrated into the analysis algorithms and the optimisation procedure to achieve what has been termed feature-based optimisation.[145] When these are addressed, several advantages will make optimisation techniques more attractive to engineers in industry who are not experts in optimisation techniques. For example, most loading and boundary conditions can be automatically extracted from feature-based CAD model of a product. Also, it would be easier to automatically generate intuitive visualisation which has been identified by Hernandez et al.[146] as a key need in order for engineers in industry to be comfortable with the use of optimisation techniques. The application of geometric modelling and reasoning will allow analysis (e.g. FEA), optimisation algorithms and parametric feature-based CAD systems to be transparently and intuitively integrated. In the short term, this may mean an integrated information backbone or infrastructure[147((==Kolonay/Burton'04))] that is flexible to support changes in geometry, meshes etc and able to dynamically link with FEA or optimisation and CAD systems through data exchange of native parametric CAD formats. In the long-term, it would require an extendible integrated information infrastructure for CAD/FEA/Optimisation based on international interoperability standards such as STEP (ISO 10303).
  8. 8. Selecting an appropriate optimisation algorithm: .... ((EECS == algorithms))
  9. 9. Dynamic optimisation: .... ((EECS == evolutionary computing))
  10. 10. Education of designers: .... ((EDU == pedagogy for aero-engineering))
  11. 11. Inherent uncertainty: .... ((EECS == fuzzy sets and other AI techniques))

Section 11. Future approaches to engineering design optimisation. It is observed from the analysis presented above there are three major areas of improvement when it comes to use of computing to address engineering design optimisation: improve efficiency and speed of optimisation and use human knowledge effectively where necessary. The two following sections will discuss role of Grid and distributed computing to speed up the optimisation and involve multiple experts in the design process; and emergent computing techniques for better efficiency and speed in the optimisation. Subsection 11.1. Engineering design optimisation using grid and distributed computing. Large-scale EDO of complex mechanical systems such as aerodynamic wing design and gas turbines involve complex processes with multiple iterative steps that require huge data and computational resources to obtain satisfactory optimum solutions.[153((==Goel/Talya/Sobolewski07)),154] The use of control theory and parallel distributed computing has proved to greatly improve the speed of aerodynamic shape optimisation of supersonic aircraft design.[155] ...This section presents the advantages of using high performance computing (HPC) and grid computing for the optimisation. ... Subsection 11.2. Emergent computing techniques. Swarm intelligence was identified as a promising new.... Simulated annealing is another popular optimization technique.... Other recent approaches with potential.... Quantum computing is....

Section 12. Summary and concluding remarks. EDO ((engineering design optimization)) has evolved with time from a totally manual process to computer-based approaches. This paper proposes a classification of the optimisation problems....

As you can see from the redlinks inside the two most recent green boxen, wikipedia doesn't have any articles on the EECS-and-industrial-engineering subfield known as engineering design optimization, though we do have an article about the parent-field of Engineering_optimization ... which has four sentences. <long pause> Oven on the EECS side, doing a bit of searching for Kalyanmoy Deb and Carlos Artemio Coello Coello, the academic rockstars of this subfield, it turns out we *do* actually have an article on multi-objective optimization, but it spends 95% of the article on the mathematics of software-only MOO, as used by quants in the stock market (or the economics department). That said, it *does* mention in two paragraph at Multi-objective_optimization#Optimal_design that sometimes MOO is used in the real world, and gives one single ref, Optimization issues of the broke management system in papermaking by Ropponen Ritala Pistikopoulos in 2011 (total of 8 cites in goog-skol). Sigh. List_of_optimization_software has one (1) single aerospace package, for spaceships. Sigh.

  Anyhoo, the main point here is, SORCER-fka-FIPER was already of WP:NOTEWORTHY mention by K.Deb the rockstar of MOO, back in 2008; that guy has thousands and thousands of cites. Sobolewski and Kolonay are both in the lit-survey paper on the future of engineering design optimization as of 2008, and although the software they had both been jointly working on since the previous millenium was not specifically named, clearly they and their work are both smack-dab in the middle of #5 and #6 and #7. Are those WP:N refs for SORCER? No. Do with have a huge long list of WP:N peer-reviewed fact-checked serious professional academic papers which cover SORCER and FIPER and exertions and all that jazz, in depth? Absolutely.

  On three continents (so far!) FIPER and SORCER play a significant part in real-world mechanical/industrial CAE both classified and unclassified, the latter of which Roy et al claims was about 200 of the 1100 papers published in the engineering-design-optimization subfield back in 2008. The problem here is not that FIPER and SORCER are "too small" to be in wikipedia, the problem is that wikipedia doesn't have enough editors to make the obviously-necessary articles, and our wikiCulture doesn't seem to want those editors, either. We've been driving editors away since 2007, when the five bazillion rules were codified.[5] We have 30k active wikipedians making 5+edits/mo, trying to satisfy 500m unique readers/mo. We spend most of our time arguing about whether we can "allow" an article on something like SORCER... because we don't have the personnel to document *every* important research area... or because not *enough* newspapers have yet reported on the topic... or because *only* newspapers have reported on the topic... or because this or because that.

  The worst part is, we *have* the people who can fill the gaps, we have the experts, they came to us, and are obviously more than happy to do so.  :-/   If only we'll let them. Hope this helps. 74.192.84.101 (talk) 16:45, 4 January 2014 (UTC)

First, a note on being an effective editor: if someone asks you for a citation, give them the citations. Not paragraphs. We're all volunteers here and we're all trying to shepherd dozens or hundreds of articles. This is your passion. I understand that. But the best way you can help us get the article to a better state is by making your replies succinct.
From what I'm seeing here, a FIPER article would be uncontroversial and the SORCER material could be contained within that. Would that be ok with you? Garamond Lethet
c 19:02, 6 January 2014 (UTC)
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