Petach Tikva, Is ael, Octobe 06, 2026 –(PR.com)– Space Utilizatio · Weight Dist ibutio · Load Bala ce
Repo ted i te al esults i clude validated geomet ic epai s, QUBO–Isi g co siste cy a d a local VQE ope atio measu ed at 0.497 milliseco ds, poi ti g towa d a b oade comme cial oppo tu ity i logistics, ma ufactu i g a d i f ast uctu e optimizatio .
DecaQ has built a wo ki g adaptive e gi e fo 3D Ca go Load Pla i g & Optimizatio , add essi g a costly ope atio al challe ge: usi g available capacity effectively while satisfyi g geomet y, weight a d loadi g co st ai ts.
Ai ca go alo e is fo ecast to ge e ate $162 billio i eve ue i 2026, acco di g to IATA’s Ju e outlook. Simila pla i g challe ges exte d ac oss shippi g, t ucki g a d wa ehouses, whe e u used capacity, epeated pla i g a d loadi g adjustme ts ca y a cost.
The comme cial sig ifica ce:The comme cial ambitio is clea : solve selected optimizatio steps i a f actio of a seco d a d tu bette decisio s i to substa tial cost savi gs, ope atio al efficie cy a d competitive adva tage.
Fo ca go ope atio s, the oppo tu ity lies i bette capacity utilizatio , fewe loadi g co ectio s a d faste pla i g decisio s. Fo the wide DecaQ platfo m, this applicatio ep ese ts a co c ete step towa d add essi g costly daily optimizatio challe ges i logistics, ma ufactu i g a d i f ast uctu e.
The measu ed local VQE esult demo st ates a fast optimizatio ope atio withi the tested wo kflow. Exte di g that capability to custome ope atio s p ovides the oute towa d comme cial value th ough bette use of space, equipme t a d esou ces.
A challe ge with seve al co st ai ts to satisfy togethe
A valid loadi g pla must coo di ate:
– Physical 3D placeme t: positio s a d pe mitted o ie tatio s.– Geomet ic fit a d space utilizatio : educi g u usable gaps a d epai i g p ot usio s.– Loadi g-block bou da ies: keepi g ca go withi the pe mitted le gth, width a d height.– Weight dist ibutio a d load bala ce: dist ibuti g weight eve ly withi egio al a d st uctu al load limits.
Imp ovi g o e pa t of the a a geme t must p ese ve the othe equi ed co st ai ts.
What the solutio i cludes:The e gi e takes ca go dime sio s, weights a d loadi g co st ai ts as i put. It models local placeme t a d epai decisio s as a QUBO optimizatio p oblem, co ve ts that model i to a Isi g Hamilto ia , a d uses VQE o DecaQ 0.8.0 to select actio s.
The QUBO–Isi g co ve sio p ese ves the optimizatio e e gy.Selected actio s feed di ectly i to the packi g e gi e, followed by sepa ate physical-validity checks. This co ects the optimizatio esult to a checked physical a a geme t.
Challe ge model a d validatio :
400 bi a y decisio va iables: spa se capacity test passed.199 ca didate actio s a d 19,900 Isi g te ms: de se test passed.6,400 QUBO–Isi g compa iso s: ze o mismatches.
Measu ed local VQE ope atio : 0.497 milliseco ds
This timi g desc ibes the epo ted local VQE ope atio ; the capacity a d de se tests a e sepa ate epo ted esults.
Repo ted i te al achieveme ts
Local VQE: co ect epai selected; exact optimum eached fo the tested case.50/50 p ot usio cases solved, compa ed with 0/50 fo the tested baseli e.30/30 geomet ic voids epai ed, with positive volume gai .10/10 i feasible cases co ectly ejected.28 u it tests a d the full eg essio campaig : passed.Two ide tical dete mi istic builds a d clea -e vi o me t evalidatio : passed.58-file delive y a chive: all files ve ified as valid.
Computatio al scale:The bi a y model defi es app oximately 2.58 × 10^120 possible assig me ts.at o e billio states pe seco d, checki g eve y posible assig me t would take app oximately 8.2 × 10^103 yea s.
This illust ates the size of exhaustive sea ch. It is ot a measu ed u time compa iso with a optimized classical solve .
About DecaQ:DecaQ develops Digital Qua tum Computi g tech ology powe ed by a Digital Qua tum O acle. Its cloud platfo m suppo ts six algo ithm families, i cludi g VQE a d QAOA, a d offe s wo kflows fo evaluati g suppo ted wo kloads, i specti g esults a d pla i g e te p ise i teg atio .
Apply the wo ki g solutio to you ope atio sCompa ies faci g ca go load pla i g, sto age allocatio o load-bala ci g challe ges a e i vited to co tact DecaQ.ai with thei data a d co st ai ts.
B i g us you challe ge. Apply a wo ki g solutio — he e a d ow.DecaQ.ai
