Recently, a lot of studies on Multi-Objective Genetic Algorithm (MOGA), in which Genetic Algorithm is applied to Multi-objective Optimization Problems (MOPs), have been reported actively. MOGA has been also applied to engineering design fields, then it is important not only to obtain high-performance Pareto solutions but also to analyze the obtained Pareto solutions and extract some knowledge i...

The applicably of multi-objective optimization to ellipsometric data analysis is presented and a method to handle complex ellipsometric problems such as multi sample or multi angle analysis using multi-objective optimization is described. The performance of a multi-objective genetic algorithm (MOGA) is tested against a single objective common genetic algorithm (CGA). The procedure is applied to...

Damage detection has been focused by researchers because of its importance in engineering practices. Therefore, different approaches have been presented to detect damage location in structures. However, the higher the accuracy of methods is required the more complex deliberations. Based on the conventional studies, it was observed that the damage locations and its size are associated with dynam...

The advances in biological technologies make it possible to generate data for multiple conditions simultaneously. Discovering the condition-specific modules in multiple networks has great merit in understanding the underlying molecular mechanisms of cells. The available algorithms transform the multiple networks into a single objective optimization problem, which is criticized for its low accur...

abstract: this paper considers the problem of scheduling n jobs on m unrelated parallel machines with sequence-dependent setup times. to better comply with industrial situations, jobs have varying due dates and ready times and there are some precedence relations between them. furthermore sequence-dependent setup times and anticipatory setups are included in the proposed model. the objective is ...

Multi-objective optimization (MO) has been an active area of research in the last two decades. In multi-objective genetic algorithm (MOGA), the quality of newly generated offspring of the population will directly affect the performance of finding the Pareto optimum. In this paper, an improved MOGA, named SMGA, is proposed for solving multi-objective optimization problems. To increase efficiency...

background: irreversible electroporation (ire) is a novel tumor ablation technique. ire is associated with high electrical fields and is often reported in conjunction with thermal damage caused by joule heating. for good response to surgery it is crucial to produce minimum thermal damage in both tumoral and healthy tissues named non-thermal irreversible electroporation(ntire). non-thermal irrev...

This paper studies the modeling and optimization of energy use and greenhouse gas emissions of eggplant production using artificial neural network and multi-objective genetic algorithm in Guilan province of Iran. Results showed that the highest share of energy consumption belongs to diesel fuel (49.24%); followed by nitrogen (33.30%). The results indicated that a total energy input of 13910.67 ...

This paper studies the modeling and optimization of energy use and greenhouse gas emissions of eggplant production using artificial neural network and multi-objective genetic algorithm in Guilan province of Iran. Results showed that the highest share of energy consumption belongs to diesel fuel (49.24%); followed by nitrogen (33.30%). The results indicated that a total energy input of 13910.67 ...

In the multi objective problems, the good Pareto optimum solutions should have the following characteristics; the solutions should be close to the real Pareto front, the solutions should not be concentrated but should be widespread and the solutions should have the optimum solutions of every single objective function. ”Distributed Cooperation model of Multi-Objective Genetic Algorithm (DCMOGA)”...