# Proof of Optimum (PoO): Consensus Model Based on Fairness and Efficiency in Blockchain
## 1 Introduction
As a result, the PoW algorithm is criticized for its weaknesses such as high energy consumption, lack of decentralization, and variability in transaction confirmation time. The use of PoO in building a blockchain model has several positive effects on its stability. First, PoO reduces the energy consumption and computational resources required to create new blocks compared to PoW. This reduces the incentive for miners to enter a race to solve complex computational problems and allows more participants to contribute to the network. Second, PoO allows for a more equitable distribution of block rewards and reduces the centralization of mining power, which can lead to a more secure and decentralized blockchain network. Third, using TSP in PoO provides a more flexible and adaptive approach to consensus than PoW. Overall, the use of PoO can increase the efficiency, fairness, and security of a blockchain network, leading to a more stable and sustainable system. Proof of Optimum (PoO) is a blockchain consensus algorithm developed against the existing problems of the traditional Proof of Work (PoW) algorithm. PoW is known to be computationally intensive and energy-consuming, which limits its scalability and accessibility to a wider range of participants. PoO aims to solve these problems by introducing a new approach that utilizes the Traveling Salesman Problem (TSP) and genetic algorithms. The TSP is a well-known optimization problem that has been studied for decades, and genetic algorithms are powerful optimization techniques that have been successfully applied to various problem domains. By using these techniques, PoO can achieve consensus more efficiently and on a larger scale, making it a promising alternative to PoW. Additionally, PoO's approach also provides a degree of fairness in the distribution of rewards for participants, further increasing its appeal as a consensus algorithm. Overall, PoO's motivation lies in improving the scalability, accessibility, and fairness of blockchain systems, which are crucial for their widespread adoption and success in the future [4]. The following topics are explained in detail in the remaining sections of this study. * A new blockchain consensus model called Proof of Optimum, which aims to direct the extra processing power spent in PoW to find suitable solutions with optimization algorithms has been detailed. * In the blockchain network in general, clients, that is, nodes, compete to create blocks. In this study, the traveling salesman (TSP) problem was selected as an example of the type of problem to be solved. The genetic algorithm is considered a solution algorithm within the framework of the PoO model. It was asked to solve the problem with a determined population, iteration and other parameters. As a result, block creation was achieved over the solution fitness value, intensity and duration values. In addition, the algorithm and model structure were tested through decentralization. * Any artificial intelligence algorithm used for solving a desired optimization problem can be used in the study. The PoO model was proposed as a new consensus model under the puzzle setup involving the TSP in this study. * In the study, the main concepts of blockchain technology and consensus algorithms were first mentioned. Differences between consensus algorithms were indicated. * Information collected on applying artificial intelligence in blockchain consensus algorithms and optimization by reviewing the literature. * Suitability, density, and time values obtained in TSPs solved by the algorithms used by nodes to determine the competition between the nodes were explained, as well as their purpose. * A general equation was given to ascertain how the competition related to PoO was concluded, that is, how to determine the node that would create the block. * Experiments were evaluated from two different perspectives: block creation time and decentralization.