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Showing 5 results for Ghasemi

Maryam Ghasemi, Mehdi Seifbarghy, Nezir Aydin, Wichai Chattinnawat,
Volume 0, Issue 0 (IJIEPR 2024)
Abstract

One of the most important issues regarding community health is animal health, followed by the health of animal products. Providing a sustainable environment for production facilities like livestock centers is important. In this study, we have proposed designing four fuzzy inference systems for managing the sustainability of livestock centers. The first, second, and third systems are applied for the economic, social, and environmental dimensions. The fourth is for a system whose output is the sustainability level while its inputs are the three addressed sustainability dimensions. We found that by increasing each sustainability dimension, the sustainability level increases

Ali Salmasnia, Ebrahim Ghasemi, Hadi Mokhtari,
Volume 27, Issue 4 (IJIEPR 2016)
Abstract

This study aims to select optimal maintenance strategy for components of an electric motor of the National Iranian Oil Refining and Distribution Company. In this regard, a method based on revised multi choice goal programming and analytic hierarchy process (AHP) is presented. Since improving the equipment reliability is an important issue, reliability centered maintenance (RCM) strategies are introduced in this paper. Furthermore, on one hand, we know that maintenance cost consists of a considerable percentage of production cost; on the other hand, the risk of equipment failure is a main factor on personnel’s safety. Consequently, the cost and risk factors are selected as important criteria of maintenance strategies.


Mahdi Bashiri, Elaheh Ghasemi,
Volume 29, Issue 2 (IJIEPR 2018)
Abstract

Supplying of blood and blood products is one of the most challenging issues in the healthcare system since blood is as extremely perishable and vital good and donation of blood is a voluntary work. In this paper, we propose a two-stage stochastic selective-covering-inventory-routing (SCIR) model to supply whole blood under uncertainty. Here, set of discrete scenarios are used to display uncertainty in stochastic parameters. Both of the fixed blood center and bloodmobile facilities are considered in this study. We suppose that the number of bloodmobiles is indicated in the first stage before knowing which scenario is occurred. To verify the validation of the presented SCIR model to supply whole blood, we examine the impact of parameters variation on the model outputs and cost function using the CPLEX solver. Also the results of comparison between the stochastic approach and expected value approach are discussed.
 
Shadan Sadighbehzadi, Zohreh Moghaddas, Amirreza Keyghobadi, Mohsen Vaez-Ghasemi,
Volume 29, Issue 4 (IJIEPR 2018)
Abstract

Natural disasters and crisis are inevitable and each year impose destructive effects on human as injuries and damage to property. In natural  disasters and after the outbreak of the crisis, demand for logistical goods and services increase. Effective distribution of emergency aid could have a significant role in minimizing the damage and fatal accident. In this study, a three-level relief chain including a number of suppliers in fixed locations, candidate distribution centers and affected areas at certain points are considered. For this purpose a mixed integer nonlinear programming model is proposed for open transportation location routing problem by considering split delivery of demand. In order to solve a realistic problem, foregoing parameters are considered as fuzzy in our proposed mode. The objectives of the proposed model include total cost minimization, minimization of the maximum travel time of
vehicles and minimization of unmet demands. In order to solve the problem of the proposed model, fuzzy multi-objective planning is used. For efficiency and effectiveness of the proposed model and solution approach, several numerical examples are studied. Computational results show the effectiveness and efficiency of the model and the proposed approach.
Amir Mohamadghasemi, Abdollah Hadi-Vencheh, Farhad Hosseinzadeh Lotfi,
Volume 32, Issue 4 (IJIEPR 2021)
Abstract

Preventive maintenance (PM) of machines has the critical role in a factory or enterprise. It decreases number of failures, increases reliability, as well as minimizes costs of production systems.  The managers’ duty of maintenance section is to prioritize machines and then, implement PM programs for them. Since machines have the different measures with respect to the maintenance costs, reliability, mean time between failures (MTBF), availability of spare parts, etc., the machines evaluation problem can be considered as a multiple criteria decision-making (MCDM) problem. Accordingly, the MCDM techniques can be applied to solve them. The aim of this paper is to extend the ELECTRE III (eLimination et choix traduisant la realite´– elimination and choice translation reality) method to interval type-2 fuzzy sets (IT2FSs) using curved (such as Gaussian) membership functions (MFs). The extended ELECTRE III methodology is then utilized to a maintenance group MCDM (GMCDM) matrix including the quantitative and qualitative criteria. In the proposed approach, the criteria weights, the assessment of alternatives with respect to criteria, and the thresholds are stated with Gaussian interval type-2 fuzzy sets (GIT2FSs). In order to show the effectiveness and applicability of the proposed approach, a case study and an illustrative example are exhibited using real decision-making problems. Due to the high correlation coefficients between our method and the others, as well as the results obtained by the proposed method, it can be taken into account as a valid and reliable approach to prioritize machines for PM.

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