An overview of interval arithmetical tools and basic techniques is presented that can be used to construct deterministic global optimization algorithms. These tools are applicable to unconstrained and constrained optimization as well as to nonsmooth optimization and to problems over unbounded domains. Since almost all interval based global optimization algorithms use branch-and-bound methods wi...

The problem of optimally designing a trajectory for a space mission is considered in this paper. Actual mission design is a complex, multidisciplinary and multi-objective activity with relevant economic implications. In this paper we will consider some simplified models proposed by the European Space Agency as test problems for global optimization. We show that many trajectory optimization prob...

Remora Optimization Algorithm (ROA) is a metaheuristic optimization algorithm, proposed in 2021, which simulates the parasitic attachment, experiential attack, and host feeding behavior of remora ocean. However, performance ROA not very good. Considering habits that rely on to find food, order improve ROA, we designed new host-switching mechanism. By adding mechanism, joint opposite selection, ...

Particle swarm optimization (PSO) has witnessed giant success in problem optimization. Nevertheless, its performance seriously degrades when coping with problems a lot of local optima. To alleviate this issue, paper designs predominant cognitive learning particle (PCLPSO) method to effectively tackle complicated problems. Specifically, for each particle, new promising exemplar is constructed by...

In many practical decision-making problems it happens that functions involved in optimization process are black-box with unknown analytical representations and hard to evaluate. In this paper, a global optimization problem is considered where both the goal function f(x) and its gradient f (x) are black-box functions. It is supposed that f (x) satisfies the Lipschitz condition over the search hy...

This paper proposes a modified sine cosine algorithm (MSCA) for discrete sizing optimization of truss structures. The original sine cosine algorithm (SCA) is a population-based metaheuristic that fluctuates the search agents about the best solution based on sine and cosine functions. The efficiency of the original SCA in solving standard optimization problems of well-known mathematical function...

Particle Swarm Optimization (PSO) is a metaheuristic optimization algorithm that owes much of its allure to its simplicity and its high effectiveness in solving sophisticated optimization problems. However, since the performance of the standard PSO is prone to being trapped in local extrema, abundant variants of PSO have been proposed by far. For instance, Fuzzy Adaptive PSO (FAPSO) algorithms ...

Optimization of turning process is a non-linear optimization with constrains and it is difficult for the conventional optimization algorithms to solve this problem. The purpose of present study is to demonstrate the potential of Imperialist Competitive Algorithm (ICA) for optimization of multipass turning process. This algorithm is inspired by competition mechanism among imperialists and coloni...

In this paper, the global optimization problem miny∈S F (y) with S being a hyperinterval in R and F (y) satisfying the Lipschitz condition with an unknown Lipschitz constant is considered. It is supposed that the function F (y) can be multiextremal, non-differentiable, and given as a ‘black-box’. To attack the problem, a new global optimization algorithm based on the following two ideas is prop...