@article { author = {Rafiee, Batool and Shishehbori, Davood and Hosseini Nasab, Hassan}, title = {Tackling uncertainty in safety risk analysis in process systems: The case of gas pressure reduction stations}, journal = {Journal of Industrial and Systems Engineering}, volume = {13}, number = {Special issue: 16th International Industrial Engineering Conference}, pages = {1-15}, year = {2020}, publisher = {Iranian Institute of Industrial Engineering}, issn = {1735-8272}, eissn = {2717-3380}, doi = {}, abstract = {Industrial plants are subjected to very dangerous events. Therefore, it is very essential to carry out an efficient risk and safety analysis. In classical applications, risk analysis treats event probabilities as certain data, while there is much penurious knowledge and uncertainty in generic failure data that will lead to biased and inconsistent alternative estimates. Then, in order to achieve a better fitting with systems condition, uncertainty needs to be considered. One of the most usual analytical methods that have been widely applied in the field of risk analysis is the technic of failure mode and effects analysis (FMEA). The usage of this method is in identifying and abolishing the multiple failure modes in various phases of system, from the product design to production of the industries system operation. To solve the shortcomings in the traditional FMEA method, we propose an innovative approach consisted of Dempster Shafer evidence theory (DST) and FMEA to provide a more efficient way for failure mode identification and prioritization. The proposed methodology in this study can well capture imprecise opinions and can prioritize failure modes considering uncertainties. City Gate Station (CGS) of Yazd Province was used to prove the practical application and validity of the proposed risk analysis methodology. Results showed that the proposed method is effective and practical for real engineering purposes.}, keywords = {Risk Analysis,Failure mode and effect analysis (FMEA),Uncertainty,Dempster Shafer evidence theory (DST),City Gate Station (CGS)}, url = {https://www.jise.ir/article_111692.html}, eprint = {https://www.jise.ir/article_111692_78fefe4c8d0d7c2243f75c620fa39863.pdf} } @article { author = {Rokhsari, Alireza and Esfahanipour, Akbar and Ardehali, Morteza}, title = {Computing optimal subsidies for Iranian renewable energy investments using real options}, journal = {Journal of Industrial and Systems Engineering}, volume = {13}, number = {Special issue: 16th International Industrial Engineering Conference}, pages = {16-29}, year = {2020}, publisher = {Iranian Institute of Industrial Engineering}, issn = {1735-8272}, eissn = {2717-3380}, doi = {}, abstract = {For the valuation of the renewable energy investments, providing private investors with a financial incentive to accelerate their investment is a very significant issue. Financial subsidies are known by the majority of the people to be one of the most important drivers in renewable energy expansion and one of the main reasons which result in the development of any industry. In this paper, we present a new approach to compute the optimal subsidies over a specific time period by using the Binomial model for the Valuation of Real Options for Iranian renewable energy investments adjusted with Tax rate. We also apply linear regression method for predicting energy prices in order to allow an investor to exercise the relevant option over the timeline of the project at the optimal price. To evaluate our proposed approach, we apply it using predicted electricity prices for the next 16 years and electricity generation cost for Seid Abad, Damghan solar power plant. Our results in comparison of the base paper show that our proposed approach improves the error of subsidy’s computation by 1.57 percent since we used the predicted energy prices rather than the spot price as used before in real options’ valuation.}, keywords = {Real Options,Subsidy,renewable energy investment,binomial method}, url = {https://www.jise.ir/article_111693.html}, eprint = {https://www.jise.ir/article_111693_882106c3440c82cff80ab5c2c2499e6f.pdf} } @article { author = {Kalaei, Mahdiyeh and Saniee monfared, mohammad ali}, title = {Reliability estimation of Iran's power network}, journal = {Journal of Industrial and Systems Engineering}, volume = {13}, number = {Special issue: 16th International Industrial Engineering Conference}, pages = {30-40}, year = {2020}, publisher = {Iranian Institute of Industrial Engineering}, issn = {1735-8272}, eissn = {2717-3380}, doi = {}, abstract = {Today, the electricity power system is the most complicated engineering system has ever been made. The integrated power generating stations with power transmission lines has created a network, called complex power network. The reliability estimation of such complex power networks is a very challenging problem, as one cannot find any immediate solution methods in current literature. In this paper, we advanced a new method for estimating the reliability of such networks, which is based on 1) decomposition of the whole network into sub-networks called islands, 2) estimating each island’s reliability in exact form using the network reliability theory, and 3) assembling the islands back together to estimate the whole network reliability, again in exact form. We applied the new method on Iran’s power network with 105 generation stations and 16460 kilometres of transmission lines.}, keywords = {Reliability estimation,power network,Network Reliability,Graph theory,Complex systems}, url = {https://www.jise.ir/article_111694.html}, eprint = {https://www.jise.ir/article_111694_203f414035a1270a89805f13d5a366e2.pdf} } @article { author = {Keramatnezhad, Nayereh and Fatahi Valilai, Omid and Jafarikia, Ahmadreza}, title = {A service decomposition and definition model in cloud manufacturing systems using game theory focusing on cost accounting perspectives}, journal = {Journal of Industrial and Systems Engineering}, volume = {13}, number = {Special issue: 16th International Industrial Engineering Conference}, pages = {41-51}, year = {2020}, publisher = {Iranian Institute of Industrial Engineering}, issn = {1735-8272}, eissn = {2717-3380}, doi = {}, abstract = {Cloud manufacturing is a new paradigm which has been under study since 2010 and a vast body of research has been conducted on this topic. Among them, service composition problems are of utmost importance. However, most studies only focused on private clouds meaning the objective function is defined for just one component of the supply chain. This paper attempts to consider service composition problem by using the concept of game theory in cloud manufacturing which is the main contribution. This issue is investigated by introducing a bi-level mathematical model with emphasizing on the realization of public clouds, in which the preferences of all stakeholders in the cloud manufacturing system have been taken into consideration. Concretely, the first level is defined based on manufacturer company’s perspective while the second level is a game designed to obtain a feasible solution by making trade-offs among costs and revenues of service providers. Manufacturer tends to optimize the quality of service metrics by producing a package of operations inside the company’s environment or assigning a combination of service providers with considering clustering. Results show the model will be able to enable the trade-off mechanism among the compositions of all stakeholders’ preferences in cloud manufacturing system with focusing on cost accounting.}, keywords = {Cloud manufacturing,service decomposition,game theory,public manufacturing cloud}, url = {https://www.jise.ir/article_111695.html}, eprint = {https://www.jise.ir/article_111695_74d1df1c8e200f0002f4fb5760673501.pdf} } @article { author = {Arasteh, Abdollah}, title = {Valuing flexibility in demand-side response: A real options approach}, journal = {Journal of Industrial and Systems Engineering}, volume = {13}, number = {Special issue: 16th International Industrial Engineering Conference}, pages = {52-65}, year = {2020}, publisher = {Iranian Institute of Industrial Engineering}, issn = {1735-8272}, eissn = {2717-3380}, doi = {}, abstract = {The investment interests in the electricity industry are transmitted through various mechanisms to other economic activities. This paper considers methods for esteeming the adaptability of demand-side response (DSR) in its capacity to react to future uncertainties. The capacity to evaluate this adaptability is particularly critical for vitality frameworks speculations given their extensive and irreversible capital expenses. The primary result of this exploration is a broad survey of current real options (RO) strategies that elucidate the suppositions and use of RO for basic leadership in engineering applications. The second result is the structure of a probabilistic RO framework and operational model for DSR that evaluates its advantages as a vitality benefit for supporting diverse market price risks. The third result of this work is the improvement of a total, general and viable apparatus for making long haul multi-arranged speculation choices in future power organizes under numerous vulnerabilities.}, keywords = {electricity,Investment,Uncertainty,real options analysis,demand-side response}, url = {https://www.jise.ir/article_111696.html}, eprint = {https://www.jise.ir/article_111696_bba86def9f10ba0a12825a240b0d7d6b.pdf} } @article { author = {Esfandyari, Azadeh and Roshani, Abdolreza}, title = {Assembly line balancing problem with skilled and unskilled workers: The advantages of considering multi-manned workstations}, journal = {Journal of Industrial and Systems Engineering}, volume = {13}, number = {Special issue: 16th International Industrial Engineering Conference}, pages = {66-77}, year = {2020}, publisher = {Iranian Institute of Industrial Engineering}, issn = {1735-8272}, eissn = {2717-3380}, doi = {}, abstract = {This paper address a special class of generalized assembly line balancing in which it is assumed that there are two groups of workers: skilled and unskilled ones. The skilled workers are hired permanently while the unskilled ones can be hired temporarily in order to meet the seasonal demands. It is also assumed that more than one worker may be assigned to each workstation. To show the advantages of assigning several workers instead of single workers to each workstation in such a class of problem, a mixed integer programming formulation is presented. This model minimizes the number of temporary workers on the line as the first objective and the number of workstations as the secondary one while cycle time and the number of permanent workers are fixed. The proposed formulation is applied to solve some experimental instances found in the literature. The comparison between the optimal solutions of the proposed model and those of traditional assembly lines with a single-manned workstation indicates that our model has been able to reduce the line length on average of 24.40 per cent while the number of unskilled workers remains optimal. }, keywords = {mathematical programming,assembly line balancing problem,skilled and unskilled workers,multi-manned workstations}, url = {https://www.jise.ir/article_111697.html}, eprint = {https://www.jise.ir/article_111697_64efe2ac6ed843a070ca77cc85ab6826.pdf} } @article { author = {Ghasemian Zarini, Fatemeh and Javadian, Nikbakhsh}, title = {A multi objective mixed integer programming model for design of a sustainable meat supply chain network}, journal = {Journal of Industrial and Systems Engineering}, volume = {13}, number = {Special issue: 16th International Industrial Engineering Conference}, pages = {78-92}, year = {2020}, publisher = {Iranian Institute of Industrial Engineering}, issn = {1735-8272}, eissn = {2717-3380}, doi = {}, abstract = {In the recent decades, rapid population growth has led to the significant increase in food demand. Food supply chain has always been one of the most important and challenging management issues. Product with short age, especially foodstuffs, is the most problematic challenges for supply chain management. These challenges are mainly due to the diversity in the number of these goods, the special need for tracking the flow of goods in the supply chain and the short age of products. Designing an appropriate supply chain network for the organization will increase profitability as well as customer satisfaction. It also helps organizations to achieve competitive advantage in market. In this research, a multi-objective planning model is presented in order to design a sustainable supply chain network. The first objective function minimizes costs, the second objective function minimizes network environmental impacts, the third objective function optimizes the productivity of facilities and the fourth objective function optimizes network social impacts. In this research, in order to deal with uncertainty, the robust optimization approach is implemented. Multi-criteria decision-making methods are also used to solve the multi-objective model.}, keywords = {Supply chain management,Sustainable Supply Chain,multi objective,robust optimization}, url = {https://www.jise.ir/article_111698.html}, eprint = {https://www.jise.ir/article_111698_7337734c000b8da5c192a509165b72ca.pdf} } @article { author = {Alidoosti, Zahra and Sadegheih, Ahmad and Pishvaee, Mir Saman and Mostafaeipour, Ali}, title = {Social sustainability assessment of conversion technologies: Municipal solid waste into bioenergy using Best Worst Method}, journal = {Journal of Industrial and Systems Engineering}, volume = {13}, number = {Special issue: 16th International Industrial Engineering Conference}, pages = {93-101}, year = {2020}, publisher = {Iranian Institute of Industrial Engineering}, issn = {1735-8272}, eissn = {2717-3380}, doi = {}, abstract = {The majority of sustainability assessments of the bio based industries are primarily focused on the environmental and economic aspects, while social impacts are rarely considered. While overlooking social dimension can have a serious harmful impact across supply chains. To address this issue, this study proposes a modified systemic approach for a social sustainability impact assessment of the technology treatment for converting municipal solid waste to bioenergy based on a review on the common methodologies for assessing social impacts. To show the applicability and efficiency of the proposed framework, a sample of 8 experts were used to evaluate and prioritize social sustainability criteria, using a multi-criteria decision-making method called the ‘best worst method’ (BWM). The criteria are ranked according to their average weight obtained through BWM. The results of this study help bio industry managers, decision-makers and practitioners decide where to focus their attention during the implementation stage, to increase social sustainability in their bioenergy supply chains derived waste and move towards sustainable development.}, keywords = {Social Sustainability,Bioenergy,Best Worst Method (BWM),treatment technology}, url = {https://www.jise.ir/article_111699.html}, eprint = {https://www.jise.ir/article_111699_c8e761e6e74855ba8964ed392500e807.pdf} } @article { author = {Ebrahimi, Malihe and Tavakkoli-Moghaddam, Reza}, title = {Benders decomposition algorithm for a green closed-loop supply chain under a build-to-order environment}, journal = {Journal of Industrial and Systems Engineering}, volume = {13}, number = {Special issue: 16th International Industrial Engineering Conference}, pages = {102-111}, year = {2020}, publisher = {Iranian Institute of Industrial Engineering}, issn = {1735-8272}, eissn = {2717-3380}, doi = {}, abstract = {Nowadays, researches pay more attention to environmental concerns consisted of various communities. This study proposes a multi-echelon, multi-period closed-loop supply chain (CLSC). A comprehensive model considers the selection of selection of technology and environmental effects. The supply chain is under a build-to-order (BTO) environment. So, there is not a final product inventory. Also, the returned products disassembled into reused components. The bi-objective mixed-integer linear problem is solved by a Benders decomposition algorithm by validating some numerical experiments. The convergence is also shown in the property.}, keywords = {Green supply chain,Closed-loop supply chain,technology,build-to-order,Benders decomposition algorithm}, url = {https://www.jise.ir/article_111700.html}, eprint = {https://www.jise.ir/article_111700_bfa75126292b3dea687c5670f559f852.pdf} } @article { author = {Mozaffariyan, Saeed and Sahraeian, Rashed}, title = {Single-machine scheduling considering carryover sequence-dependent setup time, and earliness and tardiness penalties of production}, journal = {Journal of Industrial and Systems Engineering}, volume = {13}, number = {Special issue: 16th International Industrial Engineering Conference}, pages = {112-120}, year = {2020}, publisher = {Iranian Institute of Industrial Engineering}, issn = {1735-8272}, eissn = {2717-3380}, doi = {}, abstract = {Production scheduling is one of the very important problems that industry and production are confronted with it. Production scheduling is often planned in the industrial environments while productivity in production can improve significantly the expansion of simultaneous optimization of the scheduling plan. Production scheduling and production are two areas that have attracted much attention in the industry literature and production and research in the operation systems. In this study, the problem of single-machine scheduling with linear earliness and tardiness costs considering the work failure, energy consumption restriction, and the allowed idleness have been investigated and a new nonlinear mathematical model has been presented for the single-machine scheduling problem. Considering complexity in solution, this problem has been regarded as NP-hard problem. However, using methods that produce optimized results, it is just suitable for small size problems. Based on this, a genetic algorithm has been presented for solving this problem in average and large sizes. Numerical samples show that the presented algorithm is effective and efficient.}, keywords = {Single-machine scheduling,energy consumption restriction,Earliness and tardiness penalties}, url = {https://www.jise.ir/article_111701.html}, eprint = {https://www.jise.ir/article_111701_23e9aa4c3380c70770cd3557bc65c3c3.pdf} } @article { author = {Aghajani, Farshad and Mirzapour al-e-hashem, Mohammad Javad}, title = {A multi-objective mathematical model for production-distribution scheduling problem}, journal = {Journal of Industrial and Systems Engineering}, volume = {13}, number = {Special issue: 16th International Industrial Engineering Conference}, pages = {121-132}, year = {2020}, publisher = {Iranian Institute of Industrial Engineering}, issn = {1735-8272}, eissn = {2717-3380}, doi = {}, abstract = {With increasing competition in the business world and the emergence and development of new technologies, many companies have turned to integrated production and distribution for timely production and delivery at the lowest cost of production and distribution and with the least delay in delivery. By increasing human population and the increase in greenhouse gas emissions and industrial waste, in recent years the pressures of global environmental organizations have prompted private and public organizations to take action to reduce environmental pollutants. This paper presents a nonlinear mixed integer model for the production and distribution of goods with specified shipping capacity and specific delivery time for customers. The proposed model is applicable to flexible production systems; it also provides routing for the means of transportation of products, as well as the reduction of emissions from production and distribution. The model is presented, and then by mathematical linearization is transformed into a mixed integer linear model. The data of a furniture company is used to solve the linear model, and then the linear model with the company data is solved by CPLEX software. The numerical results show that as costs increase, delays are reduced and consequently, customer satisfaction increases, and as costs increase the air pollution decreases.}, keywords = {Production-distribution integration,Production scheduling,routing,Job shop,Green supply chain,timely delivery}, url = {https://www.jise.ir/article_111702.html}, eprint = {https://www.jise.ir/article_111702_e5704efbf628cfa6b73a54fc6c8fb020.pdf} }