Niroogostar Energy Optimization Research Group

Iran

Niroogostar Energy Optimization Research Group

Iran

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Mehrmanesh H.,Islamic Azad University at Tehran | Parikhi S.,Islamic Azad University at Tehran | Fazlollahtabar H.,Iran University of Science and Technology | Fazlollahtabar H.,Niroogostar Energy Optimization Research Group
International Journal of Services and Operations Management | Year: 2013

We are aiming to develop a mathematical model in a three layer supply chain using customer relationship management extracting the product life cycle factors to satisfy customers' interests. Then, the mathematical model implies the optimal number of products and the fulfillment of an activity. We consider a three layer supply chain consisting supplier, manufacturer and customers. Customers' opinions about the product life cycle are collected via a customer relationship system. The problem is modelled to minimise the total cost of the system and maximise the process capability. The proposed bi-objective model was handled using analytic hierarchy process (AHP) weighing method. Also, a linearisation is performed to facilitate optimisation process. An application example is illustrated to verify the effectiveness of the proposed methodology. © 2013 Inderscience Enterprises Ltd.


Torkjazi M.,Mazandaran University of Science and Technology | Fazlollahtabar H.,Iran University of Science and Technology | Fazlollahtabar H.,Niroogostar Energy Optimization Research Group | Mahdavi I.,Mazandaran University of Science and Technology
Journal of Intelligent and Fuzzy Systems | Year: 2014

Optimizing an uncertain multi-objective unconstrained mathematical model is proposed. One way to optimize multi objective mathematical models is to employ utility functions for the objectives. Recent studies on utility based multi objective optimization consider only one utility function for each objective. But, in reality it is not reasonable to have a unique utility function corresponding to each objective function. Here, an unconstrained multi objective mathematical model is considered in which several utility functions are associated for each objective. A fuzzy probabilistic approach is incorporated to investigate the uncertainty of the utility functions for each objective. Since these utility functions are uncertain and in fuzzy form, the total utility function of the problem is a fuzzy nonlinear mathematical model. While, there are not any conventional approaches to solve such a model, a defuzzification method to change the total utility function to a crisp nonlinear model is employed. Meanwhile, α-cut method is applied to defuzzify the conditional utility functions. Then, an existing method to optimize the final single objective nonlinear model is adapted. The obtained results show that by changing the utility functions regarding to the dynamism of the environment, the method is still capable to provide the solutions accordingly. The effectiveness of the proposed approach is shown by solving a test problem.© 2014 - IOS Press and the authors. All rights reserved.


Fazlollahtabar H.,Iran University of Science and Technology | Fazlollahtabar H.,Niroogostar Energy Optimization Research Group | Aghasi E.,Guilan University
International Journal of Services and Operations Management | Year: 2014

In this paper, an integrated decision model is proposed to aid the marketing team of a company to improve the services. The decision is based on customers' satisfaction measures being related to the different services the company offers to its customers. Thus, a multi criteria (MC) evaluation of the company's performances based on different satisfaction measures is formed. Here, a two stage mechanism is proposed. First, the service purification with respect to some criteria is performed. Due to dynamism of the market changes and customers' opinions, a stochastic multi-criteria acceptability analysis (SMAA) is employed to purify the services. Then, a non-linear mathematical program is utilised to determine the services with more profits. The applicability and validity of the proposed model is illustrated in a case study. Copyright © 2014 Inderscience Enterprises Ltd.


Salarian R.,Mazandaran University of Science and Technology | Fazlollahtabar H.,Iran University of Science and Technology | Fazlollahtabar H.,Niroogostar Energy Optimization Research Group | Mahdavi I.,Mazandaran University of Science and Technology
International Journal of Services and Operations Management | Year: 2014

In this paper, a mathematical model is developed to formulate a cellular manufacturing system with uncertain parameters. In this model, the processing time is a random variable following normal probability distribution, demand is a random variable following normal probability distribution and the inter-arrival time for part is a random variable following exponential probability distribution. The objective of the proposed mathematical model is to configure machines' layout in cells so that the inter-cell movements are minimised and the bottlenecks are breakthrough. The applicability of the proposed mathematical programme is illustrated using numerical examples. Two numerical examples are shown in small and large sizes to emphasise the capability of the mathematical model for handling different problem sizes. Copyright © 2014 Inderscience Enterprises Ltd.

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