Natural laminar-flow (NLF) airfoils are one of the most promising technologies for extending range and endurance aircrafts. However, there is a lack methods optimization based on surface contamination that destroys laminar flow. In order to solve this problem, robust process proposed using Non-dominated Sorting genetic algorithm- II (NSGA-II) evolutionary algorithm, Monte Carlo simulation combi...

For the multiple automated guided vehicle (multi-AGV) routing problems in warehousing link of logistics, where optimization objective is to minimize both number AGVs used and maximum pickup time simultaneously, a nondominant sorting differential evolution (NSDE) algorithm proposed. In encoding decoding stages, point area divided. are allocated each region according proposed rule based on avoidi...

Atmospheric pollutants mainly produced by thermal power plants compel to utilize green energy sources such as renewable and hydroelectric in a system. But due blinking behavior of very high rate outages, it has detrimental consequence on overall grid. Demand side management (DSM) programs decrease cost improve system security. This study proposes non-dominated sorting genetic algorithm-II (NSGA...

This study proposes a bi-objective model for capacitated multi-vehicle allocation of customers to potential distribution centers (DCs).The optimization objectives are to minimize transit time and total cost including opening cost, assumed for opening potential DCs and shipping cost from DCs to the customers where considering heterogeneous vehicles lead to a more realistic model and cause more c...

In the paper, a novel stochastic Multi-Objective Self-Organizing Migrating Algorithm (MOSOMA) is introduced. For the search of optima, MOSOMA employs a migration technique used in a single-objective Self Organizing Migrating Algorithm (SOMA). In order to obtain a uniform distribution of Pareto optimal solutions, a novel technique considering Euclidian distances among solutions is introduced. MO...

NSGA ( [5]) is a popular non-domination based genetic algorithm for multiobjective optimization. It is a very effective algorithm but has been generally criticized for its computational complexity, lack of elitism and for choosing the optimal parameter value for sharing parameter σshare. A modified version, NSGAII ( [3]) was developed, which has a better sorting algorithm , incorporates elitism...

We address the problem of optimizing a spacecraft trajectory by using three different multi-objective evolutionary algorithms: i) Non-dominated sorting genetic algorithm, ii) Pareto-based ranking genetic algorithm, and iii) Strength Pareto genetic algorithm. The trajectory of interest is an orbit transfer around a central body when the spacecraft uses a lowthrust propulsion system. We use a Lya...

The current overall layout planning model matrix of landscape ceramic sculpture is generally unidirectional, and the efficiency low, resulting in a decline optimization ratio model. Therefore, design verification analysis sculpture’s based on Nondominated Sorting Genetic Algorithm (NSGA - II) algorithm proposed. According to actual needs standards, first set basic points, establish cross-planni...

This paper presents NSGA-PINN, a multi-objective optimization framework for the effective training of physics-informed neural networks (PINNs). The proposed uses non-dominated sorting genetic algorithm (NSGA-II) to enable traditional stochastic gradient algorithms (e.g., ADAM) escape local minima effectively. Additionally, NSGA-II enables satisfying initial and boundary conditions encoded into ...

In this study, our aim is to predict the compositions of zinc electroplating bath using machine learning method and optimize organic additives with NSGA-II (Non-dominated Sorting Genetic Algorithm) optimization algorithm. Mask RCNN was utilized classify coated plates according their appearance. The names classes were defined as ”Full Bright”, Fail”, ”HCD Fail” ”LCD Fail”. intersection over unio...