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Showing 17 results for Hosseini

S.m. Seyed-Hosseini, M. Sabzehparvar, S. Nouri ,
Volume 18, Issue 3 (International Journal of Engineering 2007)
Abstract

Abstract: This paper presents an exact model and a genetic algorithm for the multi-mode resource constrained project scheduling problem with generalized precedence relations in which the duration of an activity is determined by the mode selection and the duration reduction (crashing) applied within the selected mode. All resources considered are renewable. The objective is to determine a mode, the amount of continuous crashing, and a start time for each activity so that all constraints are obeyed and the project duration is minimized. Project scheduling of this type occurs in many fields for instance, predicting the resources and duration of activities in software development projects. A key feature of the model is that none of the typical models can cope with the continuous resource constraints. Computational results with a set of 100 generated instances have been reported and the efficiency of the proposed model has been analyzed.

 


H. Teimory, H. MirzaHosseinian, A. Kaboli,
Volume 19, Issue 4 (IJIE 2008)
Abstract

  The advent of e-commerce has prompted many manufacturers to redesign their traditional channel structure by engaging in direct sales. In this paper, we present a dual channel inventory model based on queuing theory in a manufacturer-retailer supply chain, consisting of a traditional retail channel and a direct channel which stocks are kept in both upper and lower echelon. The system receives stochastic demand from the both channel which each channel has an independent demand arrival rate. A lost-sales model which no backorder is allowed is supposed. The replenishment lead times are assumed independent exponential random variables for both warehouse and the retail store. Under the replenishment inventory policy, the inventory position is kept constant at a base-stock level. To analyze the chain performance, an objective function included holding and lost sales costs is defined. At the end, a proposed algorithm named, Best Neighborhood (BN) is used to find a good solution for inventory and the results are compared with Simulated Annealing (SA) solutions.


F. Sereshki, S.a. Hosseini, N. Aziz , I. Porter ,
Volume 19, Issue 5 (IJES 2008)
Abstract

The Outburst can be defined as a sudden release of coal and rock accompanied by large quantities of gas into the underground coal mine workings which represents a major hazard in underground coal mines. Gas drainage has been proven to be successful in reducing outburst hazards by decreasing the in-situ gas pressure. One of aspect of gas drainage from coal seams is coal matrix volume changes. Current study is primarily concerned with experimental studies related to coal volume change (coal shrinkage) under various gas types and pressures. Two types of tests were conducted on each sample, the adsorption test for coal swelling and the desorption test for coal shrinkage. The gases used in the study were CH4, CO2, CH4/CO2 (50-50% volume), and N2. In this research, tests were conducted with respect to volumetric change behavior in different gases and their corresponding comparative results were presented.


J. Jassbi, S.m. SeyedHosseini , N. Pilevari,
Volume 20, Issue 4 (IJIEPR 2010)
Abstract

Nowadays, in turbulent and violate global markets, agility has been considered as a fundamental characteristic of a supply chain needed for survival. To achieve the competitive edge, companies must align with suppliers and customers to streamline operations, as well as agility beyond individual companies. Consequently Agile Supply Chain (ASC) is considered as a dominant competitive advantage.  However, so far a little effort has been made for designing, operating and evaluating agile supply chain in recent years. Therefore, in this study a new approach has been developed based on Adaptive Neuro Fuzzy Inference System (ANFIS) for evaluating agility in supply chain considering agility capabilities such as Flexibility, Competency, Cost, Responsiveness and Quickness. This evaluation helps managers to perform gap analysis between existent agility level and the desired one and also provides more informative and reliable information for decision making. Finally the proposed model has been applied to a leading car manufacturing company in Iran to prove the applicability of the model.
Behin Elahi, Seyed Mohammad Seyed-Hosseini, Ahmad Makui,
Volume 22, Issue 2 (IJIEPR 2011)
Abstract

 

  Supplier selection,

  Multi-objective decision making,

  Fuzzy Compromise programming,

  Supply chain management,

  Quantity discount .

 

Supplier selection is naturally a complex multi-objective problem including both quantitative and qualitative factors. This paper deals with this issue from a new view point. A quantity discount situation, which plays a role of motivator for buyer, is considered. Moreover, in order to find a reasonable compromise solution for this problem, at first a multi-objective modeling is presented. Then a proposed fuzzy compromise programming is utilized to determine marginal utility function for each criterion. Also, group decision makers’ preferences have taken into account and the weight of each criterion has been measured by forming pair-wise comparison matrixes. Finally the proposed approach is conducted for a numerical example and its efficacy and efficiency are verified via this section. The results indicate that the proposed method expedites the generation of compromise solution .


Mohammad Saber Fallahnezhad, Hasan Hosseini Nasab,
Volume 22, Issue 3 (IJIEPR 2011)
Abstract

 In this research, a new control policy for the acceptance sampling problem is introduced. Decision is made based on the number of defectives items in an inspected batch. The objective of the model is to find a constant control level that minimizes the total costs, including the cost of rejecting the batch, the cost of inspection and the cost of defective items. The optimization is performed by approximating the negative binomial distribution with Poisson distribution and using the properties of binomial distribution. A solution method along with numerical demonstration on the application of the proposed methodology is presented. Furthermore, the results of sensitivity analysis show that the proposed method needs a large sample size .


Parviz Fattahi, Seyed Mohammad Hassan Hosseini, Fariborz Jolai, Azam Dokht Safi Samghabadi,
Volume 25, Issue 1 (IJIEPR 2014)
Abstract

A three stage production system is considered in this paper. There are two stages to fabricate and ready the parts and an assembly stage to assembly the parts and complete the products in this system. Suppose that a number of products of different kinds are ordered. Each product is assembled with a set of several parts. At first the parts are produced in the first stage with parallel machines and then they are controlled and ready in the second stage and finally the parts are assembled in an assembly stage to produce the products. Two objective functions are considered that are: (1) to minimizing the completion time of all products (makespan), and (2) minimizing the sum of earliness and tardiness of all products (∑_i▒(E_i∕T_i ) . Since this type of problem is NP-hard, a new multi-objective algorithm is designed for searching locally Pareto-optimal frontier for the problem. To validate the performance of the proposed algorithm, in terms of solution quality and diversity level, various test problems are made and the reliability of the proposed algorithm, based on some comparison metrics, is compared with two prominent multi-objective genetic algorithms, i.e. NSGA-II and SPEA-II. The computational results show that performance of the proposed algorithms is good in both efficiency and effectiveness criterions.
Pro Seyed Mohammad SeyedHosseini, Dr Kaveh Mohamad Cyrus, Mr Kaveh Fahimi, Dr Hassan Badkoobehi,
Volume 26, Issue 2 (IJIEPR 2015)
Abstract

Today’s competition is promoted from firm against firm to supply chain versus supply chain, globalization and competition is a common phenomenon so each organization should make its supply chain as a weapon against the others, in doing so this paper presented a conceptual, graphical, step by step methodology to construct supply chain strategies by integrating strategic management’s theories, application and analysis and supply chain point of view to help managers to compete in the market.

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Dr. Yahia Zare Mehrjerdi, Amir Ebrahimi Zade, Dr. Hassan Hosseininasab,
Volume 26, Issue 3 (IJIEPR 2015)
Abstract

Abstract One of the basic assumptions in hub covering problems is considering the covering radius as an exogenous parameter which cannot be controlled by the decision maker. Practically and in many real world cases with a negligible increase in costs, to increase the covering radii, it is possible to save the costs of establishing additional hub nodes. Change in problem parameters during the planning horizon is one of the key factors causing the results of theoretical models to be impractical in real world situations. To dissolve this problem in this paper a mathematical model for dynamic single allocation hub covering problem is proposed in which the covering radius of hub nodes is one of the decision variables. Also Due to NP-Hardness of the problem and huge computational time required to solve the problem optimally an effective genetic algorithm with dynamic operators is proposed afterwards. Computational results show the satisfying performance of the proposed genetic algorithm in achieving satisfactory results in a reasonable time. Keywords: hub location problem, dynamic hub covering problem, flexible covering radius, dynamic genetic algorithm.

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H Hasan Hosseini Nasab, Hamid Reza Kamali,
Volume 26, Issue 4 (IJIEPR 2015)
Abstract

This article addresses a single row facility layout problem where the objective is to optimize the arrangement of some rectangular facilities with different dimensions on a line. Regarding the NP-Hard nature of the considered problem, a hybrid meta-heuristic algorithm based on simulated annealing has been proposed to obtain a near optimal solution. A number of test problems are randomly generated and the results obtained by the proposed hybrid meta-heuristic are compared with exact solutions. The results imply that the proposed hybrid method provides more efficient solutions for the large-sized problem instances.

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Seyed Mohammad SeyedHosseini, Mohammad Mahdavi Mazdeh, Dr. Ahmad Makui, Seyed Mohammad Ghoreyshi,
Volume 27, Issue 1 (IJIEPR 2016)
Abstract

In any supply chain, distribution planning of products is of great importance to managers. With effective and flexible distribution planning, mangers can increase the efficiency of time, place, and delivery utility of whole supply chain. In this paper, inventory routing problem (IRP) is applied to distribution planning of perishable products in a supply chain. The studied supply chain is composed of two levels a supplier and customers. Customers’ locations are geographically around the supplier location and their demands are uncertain and follow an independent probability distribution functions. The product has pre-determined fixed life and is to be distributed among customers via a fleet of homogenous vehicles. The supplier uses direct routes for delivering products to customers. The objective is to determine when to deliver to each customer, how much to deliver to them, and how to assign them to vehicle and routes. The mentioned problem is formulated and solved using a stochastic dynamic programming approach. Also, a numerical example is given to illustrate the applicability of proposed approach.


Seyyed-Mahdi Hosseini-Motlagh, Sara Cheraghi, Mohammadreza Ghatreh Samani,
Volume 27, Issue 4 (IJIEPR 2016)
Abstract

The eternal need for humans' blood as a critical commodity makes the healthcare systems attempt to provide efficient blood supply chains (BSCs) by which the requirements are satisfied at the maximum level. To have an efficient supply of blood, an appropriate planning for blood supply chain is a challenge which requires more attention. In this paper, we address a mixed integer linear programming model for blood supply chain network design (BSCND) with the need for making both strategic and tactical decisions throughout a multiple planning periods. A robust programming approach is devised to deal with inherent randomness in parameters data of the model. To illustrate the usefulness of the model as well as its solution approach, it is tested into a set of numerical examples, and the sensitivity analyses are conducted. Finally, we employ two criteria: the mean and standard deviation of constraint violations under a number of random realizations to evaluate the performance of both the proposed robust and deterministic models. The results imply the domination of robust approach over the deterministic one.


Amir-Mohammad Golmohammadi, Mahboobeh Honarvar, Hasan Hosseini-Nasab, Reza Tavakkoli-Moghaddam,
Volume 29, Issue 2 (IJIEPR 2018)
Abstract

The fundamental function of a cellular manufacturing system (CMS) is based on definition and recognition of a type of similarity among parts that should be produced in a planning period. Cell formation (CF) and cell layout design are two important steps in implementation of the CMS. This paper represents a new nonlinear mathematical programming model for dynamic cell formation that employs the rectilinear distance notion to determine the layout in the continuous space. In the proposed model, machines are considered unreliable with a stochastic time between failures. The objective function calculates the costs of inter and intra-cell movements of parts and the cost due to the existence of exceptional elements (EEs), cell reconfigurations and machine breakdowns. Due to the problem complexity, the presented mathematical model is categorized in NP-hardness; thus, a genetic algorithm (GA) is used for solving this problem. Several crossover and mutation strategies are adjusted for GA and parameters are calibrated based on Taguchi experimental design method. The great efficiency of the proposed GA is then demonstrated via comparing with particle swarm optimization (PSO) and the optimum solution via GAMS considering several small/medium and large-sized problems. 


Seyyed-Mahdi Hosseini-Motlagh, Mina Nouri-Harzvili, Roza Zirakpourdehkordi,
Volume 30, Issue 3 (IJIEPR 2019)
Abstract
Amir-Mohammad Golmohammadi, Mahboobeh Honarvar, Guangdong Guangdong, Hasan Hosseini-Nasab,
Volume 30, Issue 4 (IJIEPR 2019)
Abstract

There is still a great deal of attention in cellular manufacturing systems and proposing capable metaheuristics to better solve these complicated optimization models. In this study, machines are considered unreliable that life span of them follows a Weibull distribution. The intra and inter-cell movements for both parts and machines are determined using batch sizes for transferring parts are related to the distance traveled through a rectilinear distance. The objectives minimize the total cost of parts relocations and maximize the processing routes reliability due to alternative process routing. To solve the proposed problem, Genetic Algorithm (GA) and two recent nature-inspired algorithms including Keshtel Algorithm (KA) and Red Deer Algorithm (RDA) are employed. In addition, the main innovation of this paper is to propose a novel hybrid metaheuristic algorithm based on the benefits of aforementioned algorithms. Some numerical instances are defined and solved by the proposed algorithms and also validated by the outputs of exact solver. A real case study is also utilized to validate the proposed solution and modeling algorithms. The results indicate that the proposed hybrid algorithm is more appropriate than the exact solver and outperforms the performance of individual ones.

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