Papers by Hossein Babazadeh
Soft Computing, 2018
The consideration of this study is devoted to deal with the straight and U-shaped assembly line b... more The consideration of this study is devoted to deal with the straight and U-shaped assembly line balancing problems (ALBPs). The ALBP involves allocation of required tasks to a set of workstations, so that objective functions being optimized are subjected to set of constraint. While many efforts have been dedicated in the literature to develop deterministic model of the assembly line, the attention is not considerably paid to those in uncertain circumstances. In this paper, along with proposing a novel fuzzy model for ALBP, triangular fuzzy numbers are deployed with to respect vagueness and uncertainty subjected to the task processing times. For this purpose, two conflicting objectives are considered simultaneously with regard to set of constraints, so that the efficiency of the line has to be maximized. To solve the problem, a modified NSGA-II, which utilized a new repairing mechanism, is proposed in response to the need of appropriate method treating such complicated problems. The validity of the proposed model and algorithm is evaluated and proved though a benchmark test problem. The obtained results reveal that in contrast to benchmark that applied an exact solution procedure, the proposed algorithm is capable of delivering the astonishing solutions in a more effective procedure. Along with the use of NSGA-II, in this study, three well-known meta-heuristic algorithms, namely PESA-II, NSACO and NPGA-II, are also employed for solving the problem in order to evaluate the effectiveness of the proposed algorithm, so that the results demonstrate the high performance for the NSGA-II over them. Finally, in light of the obtained results, this study offers an efficient framework enabling the decision maker to handle uncertainty in ALBPs along with the use of an efficient algorithm to solve them.
Journal of Computational and Applied Mathematics, 2019
The portfolio optimization literature has spent a little effort to consider the fat tail characte... more The portfolio optimization literature has spent a little effort to consider the fat tail characteristic of asset returns as well as their extreme events. To remove such shortcomings, in this paper, a novel portfolio optimization model is developed in which Value at Risk (VaR) is utilized as a risk measure to account extreme risk so that VaR is estimated use of Extreme Value Theory (EVT). To enrich the practicality of our proposed model, set of real trading constraints are considered such as cardinality, budget, floor and ceiling constraints. Since these modifications lead to a non-convex NP-hard problem which is computationally difficult, a new design of Non-dominated Sorting Genetic Algorithm (NSGA-II) is proposed to solve it. To evaluate the performance of EVT approach in our proposed mean-VaR model, three well-known alternative VaR estimation methods are also considered such as historical simulation, GARCH and t-student GARCH. Experimental results using historical daily financial market data from S & P 100 indices demonstrates that our proposed NSGA-II has great capability of treating the mean-VaR portfolio optimization problem. In addition, the validation study confirmed that our enhanced NSGA-II not only offers superior result compared with that of delivered by benchmark problem in a much lower solving time, but its performance is better than the original NSGA-II. Also, the results indicate that our proposed model outperforms other mean-VaR models especially in low risk area of Pareto front. Finally, the proposed algorithm is compared with set of Non-dominated-based algorithms including SPEA-II, NSPSO and NSACO which results illustrated that our enhanced NSGA-II suggests superior solutions rather than other algorithms.
Arabian Journal of Geosciences, 2013
The most appropriate method in designing the adsorption systems and assessing the performance of ... more The most appropriate method in designing the adsorption systems and assessing the performance of the adsorption systems is to have an idea on adsorption isotherms. Comparison analysis of linear least square method and nonlinear method for estimating the isotherm parameters was made using the experimental equilibrium data of Zn(II) and Cu(II) onto kaolinite. Equilibrium data were fitted to Freundlich, Langmuir, and Redlich-Peterson isotherm equations. In order to confirm the best-fit isotherms for the adsorption system, the data set using the chi-square (χ 2), combined with the values of the determined coefficient (r 2) was analyzed. Nonlinear method was found to be a more appropriate method for estimating the isotherm parameters. The best fitting isotherm was the Langmuir and Redlich-Peterson isotherm. The Redlich-Peterson is a special case of Langmuir when the Redlich-Peterson isotherm constant g was unity. The sorption capacity of kaolinite to uptake metal ions in the increasing order was given by Cu (4.2721 mg/g)<Zn (4.6710 mg/g).
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Papers by Hossein Babazadeh