ICO 2018 - 1st International Conference on Intelligent Computing & Optimization

Optimization is one of the most remarkable research interests within the scientific community. That is because of its wide scope covering different fields of modern life and providing effective results to obtain optimum values for mathematically modeled real-world problems. In time, optimization has been affected by rise of Artificial Intelligence and that has resulted to introduce of a separate research field of intelligent optimization. Intelligent optimization contains lots of different solution approaches, methods, and techniques to deal with real-world optimization problems by considering differently structured mathematical problem models or designed solution steps by inspiring from especially nature. Here, nature is a remarkable actor for the literature of intelligent optimization because almost all intelligent optimization techniques (in other words, algorithms), which are widely used, have been developed by inspiring from objects, dynamics and occurrences in the nature. Even some of inspirations have had an unstoppable role in designing and developing new algorithms. At this point, some mechanisms like cross-over, mutation, natural selection, which are explained under the Theory of Evolution, have caused researchers to develop some good examples of intelligent optimization algorithms.
Moving from the explanations so far, objective of this special session to gather research works regarding employment of evolutionary metaheuristic (non-problem specific) algorithms for engineering problems in one environment to form an effective and efficient brain-storming environment enabling researchers to discuss about results obtained with evolutionary meta-heuristic algorithms for optimization problems encountered with different engineering fields. In this way, it is also aimed to ensure a multidisciplinary discussion for opening minds to future ideas and works. Research works to be proposed for this special session may include use of evolutionary metaheuristic algorithms (like Genetic Algorithms, Differential Evolution, Clonal Selection Algorithm and many others) for any type of optimization problems (continuous, combinatorial, single-objective, multi-objective, constraint based, dynamic…etc.) in an engineering oriented field.