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A comparison is made between Exhaustive Search (ES) and Iterative LocalSearch (ILS). Such comparison was made using the Quantum ApproximationOptimization Algorithm (QAOA). QAOA has been extensively researched due to itsthis potential to be implemented in actual quantum hardware, and its promisingfuture in optimization problems and quantum machine learning. ES and ILSapproaches were simulated to determine the pros and cons of these techniquesfor QAOA in local (classic computer) and real simulations (IBM quantumcomputer). These classic approaches were used in QAOA to approximate theoptimal expected value in Max-Cut and Ising Spin Model (ISM) problems, both ofthese flavors have three simulated configurations called: linear, cyclic andcomplete (or full).

Comparison between the Iterative Local Search and Exhaustive Search methods applied to QAOA in Max-Cut and Ising Spin Model problems