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Showing 8 results for Paydar

I. Mahdavi, M. M. Paydar, M. Solimanpur , M. Saidi-Mehrabad,
Volume 21, Issue 2 (IJIEPR 2010)
Abstract

  This paper deals with the cellular manufacturing system (CMS) that is based on group technology concepts. CMS is defined as identifying the similar parts that are processed on the same machines and then grouping them as a cell. The most proposed models for solving CMS are focused on cell formation problem while machine layout is considered in few papers. This paper addresses a mathematical model for the joint problem of the cell formation problem and the machine layout. The objective is to minimize the total cost of inter-cell and intra-cell (forward and backward) movements and the investment cost of machines. This model has also considered the minimum utilization level of each cell to achieve the higher performance of cell utilization. Two examples from the literature are solved by the LINGO Software to validate and verify the proposed model.


Iraj Mahdavi, Behrang Bootaki, Mohammd Mahdi Bootaki, Paydar,
Volume 25, Issue 1 (IJIEPR 2014)
Abstract

Generally, human resources play an important role in manufacturing systems as they can affect the work environment. One of the most important factors affecting the human resources is being an interactional interest among the workers in the workshops. If the workers in a manufacturing cell have the highest surface of the interactional interest level, it causes a significant raise in coordination and cooperation indicators and in long time periods. In this paper, a new concept of being an interactional interest between workers in a manufacturing cell besides the ability to work with its machines is proposed and a bi-objective mathematical model to carry out this new point of view in cellular manufacturing systems is presented. Applying the ε-constraint method as an optimization tool for multi-objective mathematical programming, a comprehensive numerical example is solved to exhibit the capability of the presented model.
Iraj Mahdavi, Mohammad Mahdi Paydar, Golnaz Shahabnia,
Volume 26, Issue 3 (IJIEPR 2015)
Abstract

Disasters can cause many casualties and considerable destruction mainly because of ineffective preventive measures, incomplete preparedness, and weak relief logistics systems. After catastrophic events happen, quick and effective response is of great importance, so as to having an efficient logistic plan for distributing needed relief commodities efficiently and fairly among affected people. In this paper, we propose a fuzzy multi-objective, multi-modal, multi-commodity logistic model in emergency response to disaster occurrence, to assign limited resources equitably to the infected regions in a way to minimize transfer costs of commodities as well as distribution centers activation costs, and maximizing satisfied demand. In the proposed model, we have determined the optimal place of distribution centers among candidate points to receive people donations as well as sending and receiving different kinds of relief commodities. The amount of voluntary donations is not known precisely and is estimated with uncertainty, so we have used fuzzy parameters for them. The number of victims immediately after disaster is vague and is estimated indecisively though we have considered it as a fuzzy demand. A case study has been displayed to test the properties of the optimization problem that shows efficiency of this formulation in experiment.

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Mohammad Mahdi Paydar, Zahra Hassanzadeh, Ali Tajdin,
Volume 27, Issue 3 (IJIEPR 2016)
Abstract

Currently, due to increased competition in the services and manufacturing, many companies are trying to lower price and good quality products offer to the market. In this paper, the multi-criteria decision-making techniques to evaluate and select the best supplier from among the existing suppliers. The first, hierarchical structure for selecting suppliers of raw materials used and the analytic hierarchy process to obtain the relative importance of quantitative and qualitative criteria related to green supply chain is applied.  Then, a fuzzy TOPSIS technique any raw material suppliers is ranked according to the relevant criteria. Finally, with regard to the weight of suppliers and demand of raw material and resource constraints by a multi-objective mathematical model, optimum order is determined. The objectives are to minimize the total cost, maximize amount of purchases of desirable suppliers and minimize of raw materials required are not provide. The proposed method in a case study used Food Company and the relevant results are expressed.


Mohammad Mahdi Paydar, Amir Arabsheybani, Abdul Sattar Safaei,
Volume 28, Issue 1 (IJIEPR 2017)
Abstract

Recently, sustainable supply chain management (SSCM) has become one of the important subjects in the industry and academia. Supplier selection, as a strategic decision, plays a significant role in SSCM. Researchers use different multi-criteria decision making (MCDM) methods to evaluate and select sustainable suppliers. In the previous studies, evaluation is solely based on the desirable features of suppliers and their risks are neglected. Therefore, current research uses failure mode and effects analysis (FMEA) as a risk analysis technique to consider supplier's risk in combination with the MCDM method. Practically, this study operated in two main stages. In the first stage, the score of the suppliers obtains by integration Fuzzy MOORA and FMEA. In the second stage, the output of the previous stage used as input parameters in developed mix-integer linear programming to select suppliers and order optimum quantity. Finally, to demonstrate the effectiveness of the proposed approach, a case study in a chemical industry and sensitivity analysis is presented.  


Bardia Behnia, Iraj Mahdavi, Babak Shirazi, Mohammad Mahdi Paydar,
Volume 28, Issue 3 (IJIEPR 2017)
Abstract

Nowadays, the necessity of manufacturers’ response to their customers’ needs and their fields of activities have extended widely. The cellular manufacturing systems have adopted reduced costs from mass-production systems and high flexibility from job-shop manufacturing systems, and therefore, they are very popular in modern manufacturing environments. Manufacturing systems, in addition to proper machinery and equipment, workforces and their performance play a critical role.

Staff creativity is an important factor in product development, and their interest in cooperating with each other in the work environment can help the growth and maturity of this factor. In this research, two important aspects of cellular manufacturing take into consideration: Cell formation and workforce planning. Cell formation is a strategic decision, and workforce planning is a tactical decision. Practically, these two sectors cannot be planned simultaneously, and decision making in this regard is decentralized. For this reason, a bi-level mathematical model is proposed. The first level aims to reduce the number of voids and exceptional elements, and the second level tends to promote the sense of interest between the workforces for working together, which will result in synergy and growth of the organization.


Hossein Jandaghi, Ali Divsalar, Mohammad Mahdi Paydar,
Volume 30, Issue 1 (IJIEPR 2019)
Abstract

In this research, a new bi-objective routing problem is developed in which a conventional vehicle routing problem with time windows (VRPTW) is considered with environmental impacts and heterogeneous vehicles. In this problem, minimizing the fuel consumption (liter) as well as the length of the routes (meter) are the main objectives. Therefore, a mathematical bi-objective model is solved to create Pareto's solutions. The objectives of the proposed mathematical model are to minimize the sum of distance cost as well as fuel consumption and Co2 emission. Then, the proposed Mixed-Integer Linear Program (MILP) is solved using the ε-constraint approach Furthermore, numerical tests performed to quantify the benefits of using a comprehensive goal function with two different objectives. Managerial insights and sensitivity analysis are also performed to show how different parameters of the problem affect the computational speed and the solutions’ quality.
Ebrahim Asadi-Gangraj, Fatemeh Bozorgnezhad, Mohammad Mahdi Paydar,
Volume 30, Issue 2 (IJIEPR 2019)
Abstract

In many real scheduling situations, it is necessary to deal with the worker assignment and job scheduling together. However, in traditional scheduling problems, only the machine is assumed to be a constraint and there isn’t any constraint about workers. This assumption could be due to the lower cost of workers compared to machines or the complexity of workers' assignment problems. This research proposes a flexible flow shop scheduling problem with two simultaneous issues: finding the best worker assignment, and solving the corresponding scheduling problem. We present a mathematical model that extends flexible flow shop scheduling problem to admit the worker assignment. Due to the NP-hardness of the research problem, two approximation approaches based on particle swarm optimization, named PSO and SPSO, are applied to minimize the makespan. The experimental results show that the proposed algorithms can efficiently minimize the makespan but the SPSO generates better solutions especially for large-size problems.

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