{{Short description|Optimization algorithms using quantum computing}}
'''[[Mathematical optimization]]''' deals with finding the best solution to a problem (according to some criteria) from a set of possible solutions. Mostly, the optimization problem is formulated as a minimization problem, where one tries to minimize an error which depends on the solution: the optimal solution has the minimal error. Different optimization techniques are applied in various fields such as [[mechanics]], [[economics]] and [[engineering]], and as the complexity and amount of data involved rise, more efficient ways of solving optimization problems are needed. The power of [[quantum computing]] may allow solving problems which are not practically feasible on classical computers, or suggest a considerable speed up with respect to the best known classical algorithm. Among other [[quantum algorithms]], there are '''quantum optimization algorithms''' which might suggest improvement in solving optimization problems.<ref>{{cite journal|last1=Moll|first1=Nikolaj|last2=Barkoutsos|first2=Panagiotis|last3=Bishop|first3=Lev S.|last4=Chow|first4=Jerry M.|last5=Cross|first5=Andrew|last6=Egger|first6=Daniel J.|last7=Filipp|first7=Stefan|last8=Fuhrer|first8=Andreas|last9=Gambetta|first9=Jay M.|last10=Ganzhorn|first10=Marc|last11=Kandala|first11=Abhinav|last12=Mezzacapo|first12=Antonio|last13=Müller|first13=Peter|last14=Riess|first14=Walter|last15=Salis|first15=Gian|last16=Smolin|first16=John|last17=Tavernelli|first17=Ivano|last18=Temme|first18=Kristan|title=Quantum optimization using variational algorithms on near-term quantum devices|journal=Quantum Science and Technology|date=2018|volume=3|pages= 030503|doi=10.1088/2058-9565/aab822|arxiv=1710.01022}}</ref>
