Fluid Mechanics
Abolfazl Khalkhali*; Hamed Safikhani
Abstract
In this paper, lift and drag coefficients were numerically investigated using NUMECA software in a set of 4-digit NACA airfoils. Two metamodels based on the evolved group method of data handling (GMDH) type neural networks were then obtained for modeling both lift coefficient (CL) and drag coefficient ...
Read More
In this paper, lift and drag coefficients were numerically investigated using NUMECA software in a set of 4-digit NACA airfoils. Two metamodels based on the evolved group method of data handling (GMDH) type neural networks were then obtained for modeling both lift coefficient (CL) and drag coefficient (CD) with respect to the geometrical design parameters. After using such obtained polynomial neural networks, modified non-dominated sorting genetic algorithm (NSGAII) was used for Pareto based optimization of 4-digit NACA airfoils considering two conflicting objectives such as (CL) and (CD). Further evaluations of the design points in the obtained Pareto fronts using the NUMECA software showed the effectiveness of such an approach. Moreover, it was shown that some interesting and important relationships as the useful optimal design principles involved in the performance of the airfoils can be discovered by the Pareto-based multi-objective optimization of the obtained polynomial meta-models. Such important optimal principles would not have been obtained without using the approach presented in this paper.
Optimization
N. Balaji; N. Jawahar
Abstract
This paper deals with a multi-period fixed charge production-distribution problem associated with backorder and inventories. The objective is to determine the size of the shipments from each supplier and backorder and inventories at each period, so that the total cost incurred during the entire period ...
Read More
This paper deals with a multi-period fixed charge production-distribution problem associated with backorder and inventories. The objective is to determine the size of the shipments from each supplier and backorder and inventories at each period, so that the total cost incurred during the entire period towards production, transportation, backorder and inventories is minimised. A 0-1 mixed integer programming problem is formulated. Genetic algorithm based population search heuristic, Simulated annealing based neighbourhood search heuristic and Equivalent variable cost based simple heuristic are proposed to solve the formulation. The proposed methodologies are evaluated by comparing their solutions with the lower bound solutions. The comparisons reveal that Genetic algorithm and Simulated annealing algorithm generate better solutions than the Equivalent variable cost solutions and are capable of providing solutions close to the lower bound value of the problems.
