A cco rding to the w eakness of OR in dealing w ith dynam ic op t im al p rob lem s, the ou t line of a new idea to create a new discip line, in telligen t operat ion s research ( IOR ) , has been pu t fo rw ard in th is paper by com b in ing and ino scu lat ing operat ion s research w ith art if icial in telligence (A I) asw ell as know ledge engineering (KE). The p rincip les and new m ethod to deal w ith dynam ic op t im al p rob2 lem s fo r IOR have been stated. The system st ructu re and it s f ram ewo rk ofm u lt i2agen t system to han2 dle real2t im e op t im al con t ro l in a dynam ic system have been p resen ted. The issues of theo ry and p rac2 t ice in IOR, such as know ledge rep resen tat ion fo r real p rob lem s, know ledge rep resen tat ion fo r mod2 els, modeling m ethod of case2based learn ing, modeling suppo rt system , have been studied mo re deep ly. Th is research has p romo ted the in teract ion and ino scu lat ion among OR, A I and KE, etc. , and creates a w ay fo r OR theo ry to so lve op t im al dynam ic p rob lem s