Offerings

Offerings overview

Our pri­ma­ry focus is on mathe­ma­ti­cal optimi­zation, and we offer soft­ware, ser­vices, and cour­ses on this sub­ject. Our goal is to trans­form the latest sci­en­ti­fic advance­ments into prac­ti­cal­ly valuable insight and solutions.

For this pur­po­se, we have deve­lo­ped an open and free optimi­zation soft­ware that makes for­mu­la­ting and sol­ving prac­ti­cal optimi­zation pro­blems from engi­nee­ring and eco­no­mics straight­for­ward. If the chal­lenges of your ope­ra­ti­on are not cover­ed by the stan­dard reper­toire of our soft­ware, we are also hap­py to sup­port you per­so­nal­ly and indi­vi­du­al­ly in fin­ding solu­ti­ons. This can ran­ge from simp­le advi­so­ry dis­cus­sions to rese­arch pro­jects. If you would like to deve­lop com­pe­ten­ci­es yours­elf, we offer cour­ses on optimi­zation and machi­ne learning.

Click on the icons to learn more about our services.

Further information

As a rea­di­ly acces­si­ble offe­ring to you, we have pre­pared tuto­ri­als on You­tube and made our code available for down­load on Git­hub. Both resour­ces are regu­lar­ly updated. If you have ques­ti­ons about our offe­rings or are unsu­re whe­ther we can assist you, plea­se feel free to cont­act us.

F.A.Q.

For pro­blems in the are­as of optimi­zation and machi­ne lear­ning, we pro­vi­de con­sul­ting ser­vices, soft­ware, and cour­ses. Our goal is to make modern mathe­ma­ti­cal methods prac­ti­cal­ly appli­ca­ble and to gene­ra­te real value for real-world appli­ca­ti­ons. The exch­an­ge bet­ween rese­arch and appli­ca­ti­on is important to us.

The soft­ware and con­sul­ting ser­vices are pri­ma­ri­ly inten­ded for small and medi­um-sized enter­pri­ses, espe­ci­al­ly tho­se who­se pro­blems include mathe­ma­ti­cal­ly for­mu­lable ques­ti­ons deal­ing with opti­mal decis­i­ons under uncer­tain­ty. We belie­ve that in this envi­ron­ment, we can effect spe­cial oppor­tu­ni­ties for savings, effi­ci­en­cy gains, or even enti­re­ly new solutions.

We wel­co­me your cont­act. Do not hesi­ta­te to approach us even with unre­fi­ned pro­blem for­mu­la­ti­ons or ques­ti­ons. Tog­e­ther, we will be able to cla­ri­fy the details! Sim­ply send us an email or give us a call. You can find the details here: Cont­act details.

Gre­at! We are always exci­ted about oppor­tu­ni­ties for fur­ther deve­lo­p­ment, espe­ci­al­ly regar­ding the func­tion­a­li­ties of our soft­ware and indus­tri­al appli­ca­ti­ons. We are also hap­py to assist with ques­ti­ons about the func­tion­a­li­ty, per­for­mance, and appli­ca­ti­on pos­si­bi­li­ties of optimi­zation and machi­ne lear­ning. The best way to pro­ceed is to lea­ve us an email, and we will arran­ge a mee­ting to dis­cuss your con­cerns in detail.

Hard­ware is not our exper­ti­se, and we focus exclu­si­ve­ly on soft­ware. Addi­tio­nal­ly, we pro­ba­b­ly can­not help you if you have alre­a­dy mode­led your pro­blem using sta­te-of-the-art sol­vers and found that new sci­en­ti­fic deve­lo­p­ments are neces­sa­ry for suc­cessful resolution.

The cour­ses are desi­gned for two fun­da­men­tal­ly dif­fe­rent tar­get groups. On one hand, we offer cour­ses that pro­vi­de an over­view of optimi­zation and machi­ne lear­ning, which are par­ti­cu­lar­ly sui­ta­ble for the gene­ral­ly inte­res­ted and decis­i­on-makers. Other cour­ses, howe­ver, are very detail­ed and aim to enable the appli­ca­ti­on of sta­te-of-the-art mathe­ma­ti­cal methods to prac­ti­cal pro­blems. They are aimed at experts.

Apart from your own note-taking mate­ri­als, no addi­tio­nal mate­ri­als are requi­red. Slides and IT infra­struc­tu­re are orga­ni­zed by us. The lap­tops used for pro­gramming and expe­ri­men­ting are pro­vi­ded by us. All neces­sa­ry pro­grams are alre­a­dy pre-installed.

Curr­ent­ly, this is not pos­si­ble. The cour­ses are in the plan­ning pha­se, and we expect the first cour­ses to take place in the fall of 2024. From then on, online regis­tra­ti­on will be pos­si­ble. The ran­ge of cour­ses will then be gra­du­al­ly expan­ded until all the topics lis­ted here are covered

We expect that the first fun­da­men­tal­ly func­tion­al beta ver­si­on 0.7 will be available in the win­ter of 2024 / spring of 2025. It will fea­ture a gra­phi­cal user inter­face for for­mu­la­ting, ana­ly­zing, and pre­sen­ting optimi­zation pro­blems and is sui­ta­ble for pri­va­te use.

The suite addres­ses pro­blems in the are­as of opti­mal design, opti­mal esti­ma­ti­on, and opti­mal con­trol. This includes, among other things, work­flow plan­ning, trans­por­ta­ti­on pro­blems, topo­lo­gy optimi­zation, para­me­ter optimi­zation and esti­ma­ti­on, quan­ti­fi­ca­ti­on and cons­traint of uncer­tain­ties, esti­ma­ti­on of func­tion­al rela­ti­onships and cor­re­la­ti­on struc­tures, as well as the con­trol of sys­tems in deter­mi­ni­stic, sto­cha­stic, or com­ple­te­ly unknown situa­tions. Some examp­les can be found on the homepage.

The suite is being con­ti­nuous­ly deve­lo­ped. In addi­ti­on to the gra­phi­cal user inter­face, func­tion­a­li­ties are to be imple­men­ted abo­ve all that enable its pro­fes­sio­nal use in indus­tri­al appli­ca­ti­ons and for rese­arch. This means the imple­men­ta­ti­on of fur­ther pro­blem clas­ses and the pro­vi­si­on of sol­vers, espe­ci­al­ly for mixed-inte­ger pro­blems and dyna­mic pro­gramming. Among other things, impro­ved inter­faces for data import and export are also planned.

Our soft­ware packa­ge is stored as a repo­si­to­ry on Git­Hub, whe­re it can be clo­ned. It then beco­mes available in your pro­gramming envi­ron­ment as exe­cu­ta­ble Python code. As part of our series of tuto­ri­al vide­os on You­Tube, we also crea­te a tech­ni­cal tuto­ri­al. This shows you the typi­cal pro­ce­du­re for instal­ling Python and all the neces­sa­ry sup­port pro­grams for optimi­zation, inclu­ding ours.

On our web­site, the­re is a con­ti­nuous­ly expan­ded cata­log of appli­ca­ti­ons. Refe­ren­ces are pro­vi­ded the­re — they offer a good start­ing point. High­ly recom­men­ded are the wide­ly used stan­dard works on con­vex optimi­zation [Boyd] and machi­ne lear­ning [Has­tie]. Both books are available for free and legal down­load as PDFs on the aut­hors’ homepages.

[Boyd] Boyd, S., & Van­den­berg­he, L. (2004). Con­vex Optimi­zation. Cam­bridge: Cam­bridge Uni­ver­si­ty Press.

[Has­tie] Has­tie, T., Tibs­hira­ni, R., & Fried­man, J. (2013).  The Ele­ments of Sta­tis­ti­cal Lear­ning: Data Mining, Infe­rence, and Pre­dic­tion. Ber­lin Hei­del­berg: Sprin­ger Sci­ence & Busi­ness Media.