11 A new scheme based on multi-objective hierarchical genetic algorithm (MOHGA) is proposed to extract interpretable rule-based knowledge from data. The approach is derived from the use of multiple objective genetic 13 algorithm (MOGA), where the genes of the chromosome are arranged into control genes and parameter genes. These genes are in a hierarchical form so that the control genes can mani...

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...

Decision making in engineering design can be effectively addressed by using genetic algorithms to solve multi-objective problems. These multi-objective genetic algorithms (MOGAs) are well suited to implementation in a Service Oriented Architecture. Often the evaluation process of the MOGA is compute-intensive due to the use of a complex computer model to represent the real-world system. The eme...

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...

Two techniques are combined during the design of an optimal controller: Linear Matrix Inequalities (LMIs) and Multi-objective Genetic Algorithms (MOGAs). In this paper the LMI optimization technique is used to obtain a single controller while MOGA is used to convert the controller design into a multi-objective optimization procedure. The combination of these techniques is proposed in this docum...

This paper shows how a small number of simple fuzzy if-then rules can be selected for pattern classi-cation problems with many continuous attributes. Our approach consists of two phases: candidate rule generation by rule evaluation measures in data mining and rule selection by multi-objective evolutionary algorithms. In our approach, -rst candidate fuzzy if-then rules are generated from numeric...

The primary function of hybrid direct current circuit breakers (HCBs) is to quickly interrupt fault currents protect high-voltage (HVDC) systems. To enhance the reliability and stability HVDC systems, optimal design HCBs required minimize peak current, interruption time, recovery time. Therefore, this study develops a multi-objective genetic algorithm (MOGA)-based optimization model identify pa...

In this paper we propose a two-stage Multi-Population Genetic Algorithm (MPGA) to solve parallel machine scheduling problems with multiple objectives. In the first stage, multiple objectives are combined via the multiplication of the relative measure of each objective. Solutions of the first stage are arranged into several sub-populations, which become the initial populations of the second stag...

Multi-objective genetic algorithms (MOGA) are used to optimize a low-thrust spacecraft control law for orbit transfers around a central body. A Lyapunov feedback control law called the Q-law is used to create a feasible orbit transfer. Then, the parameters in the Q-law are optimized with MOGAs. The optimization goal is to minimize both the flight time and the consumed propellant mass of the tra...

MOTIVATION With an increase in the number of known biological functions of non-coding RNAs, the importance of RNA sequence alignment has risen. RNA sequence alignment problem has been investigated by many researchers as a mono-objective optimization problem where contributions from sequence similarity and secondary structure are taken into account through a single objective function. Since ther...