masuod simkhah; kamran Feizi
Volume 12, Issue 33 , July 2015, Pages 1-25
Abstract
This paper provides a process model for supply risk management in the automotive supply chain. Process model describes why the automobile manufacturer's entry into the supply risk management process and how automobile manufacturer manages supply risk. Rely on grounded theory and based on 13 qualitative ...
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This paper provides a process model for supply risk management in the automotive supply chain. Process model describes why the automobile manufacturer's entry into the supply risk management process and how automobile manufacturer manages supply risk. Rely on grounded theory and based on 13 qualitative in-depth interviews with 10 managers and experts in Iran's automotive industry supply chain, a theoretical framework for this issue is developed. Based on this framework, the category of perceptional process explains why the automobile manufacturer's entry into the supply risk management process and four categories of bedder factors, contingency factors, goals and process of facing to the supply risk explains how automobile manufacturer manages supply risk.
Ali Morovati sharifabadi; Mahsa Namakshenas Jahromi; Alireza Ziaei Bideh
Volume 12, Issue 33 , July 2015, Pages 25-42
Abstract
The modern world causes increased pollution and environmental problems and governments and organization‘s concerns about the environment and finally creates a concept as green innovation. This paper aims to evaluate the effect of green innovation dimensions on firm performance, ...
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The modern world causes increased pollution and environmental problems and governments and organization‘s concerns about the environment and finally creates a concept as green innovation. This paper aims to evaluate the effect of green innovation dimensions on firm performance, with environmental performance as mediator. The firms in tile and ceramic industry in Yazd province are the target population of this study. This study proposes to evaluate green innovation practices with a particular focus on the managerial, process, product and technology innovation aspects. Structural equation modeling based on PLS method have been used to test the hypothesis. Results showed that green innovation dimensions including green process and technological innovation have significant effect directly on firm performance and also indirectly through the mediator role of environmental performance. Also, green management and product innovation effect only indirectly on firm performance.
Mehdi Yazdani; Mostafa Zandieh; Reza Tavakkoli-Moghaddam
Volume 12, Issue 33 , July 2015, Pages 43-74
Abstract
In this paper, the dual-resource constrained flexible job-shop scheduling problem (DRCFJSP) with objective of minimizing the makespan is investigated. Under studied problem is NP-hard and mainly includes three sub-problems. The first one is to assign each operation to a machine out ...
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In this paper, the dual-resource constrained flexible job-shop scheduling problem (DRCFJSP) with objective of minimizing the makespan is investigated. Under studied problem is NP-hard and mainly includes three sub-problems. The first one is to assign each operation to a machine out of a set of capable machines, the second one is to determine a worker among a set of skilled workers for processing each operation on the selected machine and the third one deals with sequencing the assigned operations on the machines considering workers in order to optimize the performance measure. In this paper, we provide a mathematical model for this problem and then propose a hybrid meta-heuristic algorithm for solving the problem. The proposed hybrid algorithm uses variable neighborhood search and simulated annealing algorithms to search in the solution space. Computational study with randomly generated test problems is performed to evaluate the performance of the proposed algorithm. The results show the proposed algorithms are effective approaches for solving the DRCFJSP.
Ahmad Jafarnejad; Mehrdad Yasaei
Volume 12, Issue 33 , July 2015, Pages 75-96
Abstract
Due to the changes in production and market conditions, companies are facing many pressures. One of the ways of confronting with these pressures is the concept of supply chain and increasing its flexibility to satisfy different needs of customers. Despite the importance of supply chain flexibility, lack ...
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Due to the changes in production and market conditions, companies are facing many pressures. One of the ways of confronting with these pressures is the concept of supply chain and increasing its flexibility to satisfy different needs of customers. Despite the importance of supply chain flexibility, lack of appropriate analytical models to explain the relationship between the flexibility in a system and the performance of overall system is still recognized. Therefore, in this study a mathematical model of supply chain flexibility has been presented. This research is applied and of the descriptive research types. This study is done in two phases; dimensions detection and modeling. Identified dimensions in the first phase are labor flexibility, machine flexibility, routing and process flexibility. They are important dimensions for assess each three levels; provide, produce and assemble the entire supply chain. The result of the second phase was the design of a mathematical model for each three levels, separately, but dependent on other levels by objective function. Their limitations are defined by identified dimensions in the first phase. .
Ali Mohtashami*
Volume 12, Issue 33 , July 2015, Pages 97-124
Abstract
This paper presents a multi-objective mathematical model for redundancy allocation in production systems. In many of the production and assembly lines, process times, time between failures and repaired times are generally distributed. The proposed method of this paper is able to consider time dependent ...
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This paper presents a multi-objective mathematical model for redundancy allocation in production systems. In many of the production and assembly lines, process times, time between failures and repaired times are generally distributed. The proposed method of this paper is able to consider time dependent parameters as general distribution functions by using the hybrid approach of simulation and response surface methodology. The objectives of the mathematical model are maximizing production rate, minimizing total cost and maximizing quality. In order to solve the proposed mathematical model, non-dominated sorting genetic algorithm and multiple objective particle swarm optimization are used. Numerical results indicate the effectiveness of both algorithms for generating non-dominated solutions. Moreover, comparative results indicate the superiority of the Non-dominated sorting genetic algorithm.
Magsud Amiri; , Mohammad Amin Nayebi; Oveis Zarabadipour
Volume 12, Issue 33 , July 2015, Pages 125-124
Abstract
In this paper we have developed inventory control models (r,Q) & (R,T) in multi-items environment by two objectives as minimizing costs (holding & shortage) and risk level under four constraints. These constraints include: available budge, service level, storage space & allowed shortage quantities. ...
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In this paper we have developed inventory control models (r,Q) & (R,T) in multi-items environment by two objectives as minimizing costs (holding & shortage) and risk level under four constraints. These constraints include: available budge, service level, storage space & allowed shortage quantities. Demand functions assumed normal in the study and extra demands also are backlogged. First we developed crisp models and then fuzzy stochastic models with fuzzy budge, allowed shortage quantities and shortage space which are fuzzy-stochastic parameters with normal distribution. All of fuzzy numbers are triangular typically. In this methodology we changed fuzzy-stochastic models to crisp multi objectives problem, by using difuzzification of fuzzy constraints and then solving by Fuzzy logic method. Finally we have tested an example to describe the model and methodology which is solved by LINGO package. .
Mohammad Javad Mohagheghnia; Kashi Mansoor; Alireza Daliri; Mohammad Donyaei
Volume 12, Issue 33 , July 2015, Pages 151-181
Abstract
This paper investigates the presence of long memory in the Tehran stock market, using the ARFIMA, GPH, GSP and FIGARCH models. The data set consists of daily returns, and long memory tests are carried out both for the returns and volatilities of TEPIX series. Results of the GPH, GSP and ARFIMA models ...
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This paper investigates the presence of long memory in the Tehran stock market, using the ARFIMA, GPH, GSP and FIGARCH models. The data set consists of daily returns, and long memory tests are carried out both for the returns and volatilities of TEPIX series. Results of the GPH, GSP and ARFIMA models indicate the existence of long memory in return series. Also, suggest that long memory dynamics in the returns and volatility might be modeled by using the ARFIMA–FIGARCH model. Furthermore, results of this model shoes the strong evidence of long memory, both in conditional mean and conditional variance. In addition, the assumption of non-normality is appropriate for capturing the asymmetry and tail fatness of estimated residuals. These findings suggest that the model based on the Gaussian normality assumption may be inappropriate for modeling the long memory property. Finally, it seems that the Tehran Stock Exchange (TSE) cannot be considered an efficient market in terms of the speed of information transmission. Hence, speculative earnings could be gained via predicting stock prices.
