different approaches have been proposed for feature selection to obtain suitable features subset among all features. these methods search feature space for feature subsets which satisfies some criteria or optimizes several objective functions. the objective functions are divided into two main groups: filter and wrapper methods.  in filter methods, features subsets are selected due to some measu...

The aim of this study is to optimize performance functions of turbofan engines considering the off-design model of turbofan engine as well as employing multi-objective genetic algorithm. The design variables including high-pressure compressor pressure ratio, low-pressure compressor pressure ratio, fan pressure ratio and bypass ratio are calculated in such a way that the corresponding functions ...

arguably, the natural gas transmission pipeline infrastructure in iran represents one of the largest andmost complex mechanical systems in the world. the optimization of large gas trunk lines known asigat results in reduced fuel consumption or higher capability and improves pipeline operation. in thecurrent study, a single-objective optimization was conducted for khormoj compressor station on t...

this paper considers the job scheduling problem in virtual manufacturing cells (vmcs) with the goal of minimizing two objectives namely, makespan and total travelling distance. to solve this problem two algorithms are proposed: traditional non-dominated sorting genetic algorithm (nsga-ii) and knowledge-based non-dominated sorting genetic algorithm (kbnsga-ii). the difference between these algor...

This paper uses integrated Data Envelopment Analysis (DEA) models to rank all extreme and non-extreme efficient Decision Making Units (DMUs) and then applies integrated DEA ranking method as a criterion to modify Genetic Algorithm (GA) for finding Pareto optimal solutions of a Multi Objective Programming (MOP) problem. The researchers have used ranking method as a shortcut way to modify GA to d...

delivering perishable products to customers as soon as possible and with the minimum cost has been always a challenge for producers and has been emphasized over recent years due to the global market becoming more competitive. in this paper a multi-objective mix integer non-linear programming model is proposed to maximize both profits of a distributer and the total freshness of the several produ...

in this study, under the constraint of resource-saving and environment-friendliness objective, based on multi-agent genetic algorithm, multi-objective spatial optimization (moso) model for land use allocation was developed from the view of simulating the biological autonomous adaptability to environment and the competitive-cooperative relationship. the model was applied to solve the practical m...

in this paper, a multi-objective reconfiguration problem has been solved simultaneously by a modified ant colony optimization algorithm. two objective functions, real power loss and energy not supplied index (ens), were utilized. multi-objective modified ant colony optimization algorithm has been generated by adding non-dominated sorting technique and changing the pheromone updating rule of ori...

Real world problems often present multiple, frequently conflicting, objectives. The research for optimal solutions of multi-objective problems can be achieved through means of genetic algorithms, which are inspired by the natural process of evolution: an initial population of solutions is randomly generated, then pairs of solutions are selected and combined in order to create new solutions slig...