abstract: regarding the growing use of distributed generation resources, optimal design of these units is necessary in the power system especially in the distribution network. in this paper, cuckoo optimization algorithm with multiple purposes was used to determine optimal location and size of distributed generation resources. the investigated purposes include reducing line losses, reducing med...

Many real-world search and optimization problems involve inequality and/or equality constraints and are thus posed as constrained optimization problems. In trying to solve constrained optimization problems using classical optimization methods, this paper presents a Multi-Objective Bees Algorithm (MOBA) for solving the multi-objective optimal of mechanical engineering problems design. In the pre...

With the continuous improvement of deep object detectors via advanced model architectures, imbalance problems in training process have received more attention. It is a common paradigm detection frameworks to perform multi-scale detection. However, each scale treated equally during training. In this paper, we carefully study objective detector We argue that loss level neither important nor indep...

Aerodynamic design optimization is a key aspect in aircraft design. The further evolution of advanced derivatives requires powerful toolbox. Reinforcement learning (RL) tool but has rarely been utilized the aerodynamic It can potentially obtain results similar to those human designer, by accumulating experience from training. In this work, popular RL method called proximal policy (PPO) proposed...

land cover information is one of the most important prerequisite in urban management system. in this way remote sensing, as the most economic technology, is mainly used to produce land cover maps. considering the complicated and dense urban areas in third world countries, object based approaches are suggested as an effective image processing technique. the purpose of this paper are the introduc...

In recent years, the constrained optimization problems have become a hot topic among the interest of scholars. In this paper, a new improved artificial immune algorithm is proposed and then used for solving constrained optimizations problems (COPs). This algorithm will treat these COPs as multi-objective optimization problems, and it is based on the concept of Pareto optimization to solve COPs....

this paper proposes a method to solve multi-objective problems using improved particle swarm optimization. we propose leader particles which guide other particles inside the problem domain. two techniques are suggested for selection and deletion of such particles to improve the optimal solutions. the first one is based on the mean of the m optimal particles and the second one is based on appoin...