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کاربرد نوع شرط:
- جایگاه : پژوهشی
- مجله: Iranian Journal of Chemistry and Chemical Engineering
- نوع مقاله: Journal Article
- کلمات کلیدی: Organic Solvents,Solid-liquid equilibrium,Isotactic poly (1-butene),GMDH type-neural network
- چکیده:
- چکیده انگلیسی: Isotactic poly (1-butene), ipbu-1, was synthesized by using a metallocene catalyst. The thermodynamic phase behavior of polymer–organic solvents systems is very important in every polymer application. In this paper, the solid–liquid equilibrium of ipbu-1 with different organic solvents (1-heptyne, cyclo octane) was studied by a mathematical model. By considering the experiments temperature-mole fraction results, phase diagram of the polymer solvent systems could be constructed. The temperature and activity coefficient based on mole fraction phase diagrams were predicted by using Pareto genetic design of GMDH-type neural network. The results were very encouraging and congruent with the experimental data.
- انتشار مقاله: 28-11-1390
- نویسندگان: Hossein Ghanadzadeh,Allahyar Daghbandan,Mohammd Akbarizadeh
- مشاهده
- جایگاه : پژوهشی
- مجله: International Journal of Engineering, Transactions A: Basics
- نوع مقاله: Journal Article
- کلمات کلیدی: Multi-objective,historical data,LR-FUZZY,Lp-metrics,Portfoli
- چکیده:
- چکیده انگلیسی: The optimization of investment portfolios is the most important topic in financial decision making, and many relevant models can be found in the literature. According to importance of portfolio optimization in this paper, deals with novel solution approaches to solve new developed portfolio optimization model. Contrary to previous work, the uncertainty of future returns of a given portfolio is modeled using LR-FUZZY numbers while the function of its return are evaluated using possibility theory. We used a novel Lp-metric method to solve the model. The efficacy of the proposed model is tested on criterion problems of portfolio optimization on LINGO provides a framework to optimize objectives when creating the loan portfoliso, in a search for a dynamic markets decision. In addition to, the performance of the proposed efficiently encoded multi-objective portfolio optimization solver is assessed in comparison with two well-known MOEAs, namely NSGAII and ICA. To the best of our knowledge, there is no research that considered NSGAΠ, ICA fuzzy simultaneously. Due to improve the performance of algorithm, the performance of this approach more study is probed by using a dataset of assets from the Iran’s stock market for three years historical data and PRE method. The results are analyzed through novel performance parameters RPD method. Thus, the potential of our comparison led to improve different portfolios in different generations.
- انتشار مقاله: 30-02-1398
- نویسندگان: Azadeh Kameli,Nikbakhsh Javadian,Allahyar Daghbandan
- مشاهده
- جایگاه : پژوهشی
- مجله: Advances in Industrial Engineering
- نوع مقاله: Journal Article
- کلمات کلیدی: Cessation of activities,meta-heuristic methods,Multi-mode execution,Multi-objectives particle swarm algorithm,Resources-constrained project scheduling
- چکیده:
- چکیده انگلیسی: The Multi-Mode Resource Constrains Project Scheduling Problem (MRCPSP) tries to find the best sequence of activities in a manner that involves more than one type of operating mode and in the presence of resource constraints, project’s precedence constraints must be satisfied. In each execution mode, the amount of resources and execution time are specified and different. In The Preemptive multi-mode Resource Constraints Project Scheduling Problem (P-MRCPSP), each operating mode activity can be interrupted and restarted at any time without any extra cost. In this paper, minimizing the completion time along with maximizing the current net value of the project in the P-MRCPSP are considered. After solving the problem by using Epsilon limits method, according to NP-hard problem and multi-objective model, multi-objective particle swarm optimization (MOPSO) has been developed to achieve optimum scheduling. In order to evaluate the proposed method’s efficiency, results have been compared to non-dominance genetic algorithm sorting (NSGAII) based on designed indicators. The Taguchi method has been used in experimental design, to adjust these two algorithms’ parameters. The results of the model solution show the strength of MOPSO algorithm.
- انتشار مقاله: 09-08-1395
- نویسندگان: Hamzeh Amin-Tahmasbi,Allahyar Daghbandan,Roya Bagherpour
- مشاهده