Firouzabad Institute of Higher Education

Firouzabad, Iran

Firouzabad Institute of Higher Education

Firouzabad, Iran
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Mosallaeipour S.,Eastern Mediterranean University | Mahmoodirad A.,Islamic Azad University | Niroomand S.,Firouzabad Institute of Higher Education | Vizvari B.,Eastern Mediterranean University
Soft Computing | Year: 2017

A critical problem in carton box production industries arises when size, amount and supplier of raw sheet are to be determined in an uncertain and competitive environment from sheet price point of view. This study introduces a multi-criteria mixed integer formulation to select size, amount and supplier of raw sheets used in a case study of carton box manufacturing sector in order to minimize objectives such as cost, wastage of sheets and surplus of carton boxes simultaneously. To respect the uncertain market, some parameters of the problem such as demand of the boxes, price of raw sheets are considered as fuzzy numbers. To cope with uncertainty of the introduced mathematical formulation, a possibilistic approach is applied to convert the fuzzy formulation to a crisp model. In order to tackle the multi-criteria crisp formulation, a new multi-objective solution approach is proposed to solve the problem in comparison with four multi-objective optimization approaches such as LH, TH, SO, and ABS methods of the literature. Computational experiments and sensitivity analysis which are performed on real numerical data given by study case show the superior performance of the proposed approach compared to the others. © 2017 Springer-Verlag Berlin Heidelberg


Taassori M.,Eastern Mediterranean University | Niroomand S.,Firouzabad Institute of Higher Education | Uysal S.,Eastern Mediterranean University | Hadi-Vencheh A.,Islamic Azad University at Khorasgan | Vizvari B.,Eastern Mediterranean University
Journal of Intelligent and Fuzzy Systems | Year: 2016

Network on Chip (NoC) has been suggested as an appropriate and scalable solution for System on Chip (SoC) architectures having high communication demands. In this study, we propose heuristic fuzzy based mapping approaches to decrease the power consumption and improve the performance in the NoCs. The proposed method has two steps: core to task mapping and router reduction. In the mapping stage, two algorithms are proposed; first, proposed mapping algorithm maps the tasks to cores heuristically by means of Genetic and Simulated annealing algorithms, then tries to define a cost for each mapping and choose the lowest cost in order to diminish the power dissipation in the NoCs. In the second mapping algorithm, fuzzy rules are applied to evaluate and select the best topology such that the power consumption is minimized. Fuzzy logic is used to make a better decision in terms of distance and bandwidth for tasks to cores mapping. In the second phase, since the optimum number of router resources has colossal effect on power dissipation in the NoCs, fuzzy approach is utilized to reduce the number of routers in the NoC architectures without any significant impact on the performance. To evaluate the proposed methods, we use five multimedia benchmarks. The experimental results show that heuristic and fuzzy logic methods improve the power consumption over the non-optimized NoC by up to 66 and 73, respectively. Also, the proposed fuzzy mapping algorithm along with the router reduction method compared to the presented fuzzy without router reduction approach gives on an average, 73 energy reduction. © 2016 - IOS Press and the authors.


Niroomand S.,Firouzabad Institute of Higher Education | Hadi-Vencheh A.,Islamic Azad University at Khorasgan | Mirzaei N.,Istanbul Aydin University | Molla-Alizadeh-Zavardehi S.,Islamic Azad University
International Journal of Computer Integrated Manufacturing | Year: 2016

This paper focuses on earliness and tardiness minimisation of a special case of single machine scheduling problem with common fuzzy due-date. The problem arises from a cable manufacturing system where cables are produced in different sizes and colours. The problem is generalised by considering two attributes for each product (job) and different levels for each attribute. Setup time between a pair of jobs is different when the level of one attribute or both attributes is changed, as is the case in this study. Three hybrid greedy algorithms and a genetic algorithm are introduced to solve the test problems generated for the generalised problem while Taguchi experimental design method is used to find the best level of parameters for each algorithm. Finally, the comparisons are employed to select the best method. © 2016 Taylor & Francis


Niroomand S.,Firouzabad Institute of Higher Education | Mahmoodirad A.,Islamic Azad University | Heydari A.,Firouzabad Institute of Higher Education | Kardani F.,Islamic Azad University | Hadi-Vencheh A.,Islamic Azad University at Khorasgan
Operational Research | Year: 2016

A shortest path problem on a network in the presence of fuzzy arc lengths is focused in this paper. The aim is to introduce the shortest path connecting the first and last vertices of the network which has minimum fuzzy sum of arc lengths among all possible paths. In this study a solution algorithm based on the extension principle of Zadeh is developed to solve the problem. The algorithm decomposes the fuzzy shortest path problem into two lower bound and upper bound sub-problems. Each sub-problem is solved individually in different (Formula presented.) levels to obtain the shortest path, its fuzzy length and its associated membership function value. The proposed method contains no fuzzy ranking function and also for each (Formula presented.)-cut, it gives a unique lower and upper bound for the fuzzy length of the shortest path. The algorithm is examined over some well-known networks from the literature and its performance is superior to the existent methods. © 2016 Springer-Verlag Berlin Heidelberg


Akbari M.,Islamic Azad University at Firoozkooh | Molla-Alizadeh-Zavardehi S.,Islamic Azad University | Niroomand S.,Firouzabad Institute of Higher Education
Operational Research | Year: 2017

This paper introduces a mathematical model for fixed-charge solid transportation problem for a two-stage supply chain network, considering simultaneously both variable and fixed costs. Existence of the fixed costs and thereupon NP-hardness of the problem, use of meta-heuristics is necessary. Therefore, three approaches as genetic algorithm, electromagnetism-like algorithm and charged system search in accordance with priority-based encoding are developed. Contrary to previous researches which considered conveyances for one stage supply chain, here, conveyances are considered in each stage of the supply chain network for the first time. To determine the parameters’ levels and the introduced operators of the algorithms that exhibit best solution, a Taguchi experimental design method is applied. This experimental design decreases the required number of experiments. As final experiment, the performance of the proposed algorithms are compared with each other by running them with different problem sizes. © 2017 Springer-Verlag GmbH Germany

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