@article { author = {Emami, Saeed and Barzegaran, Fatemeh and Divsalar, Ali}, title = {A Mathematical Model for Production Planning and Scheduling in a Production System: A Case Study}, journal = {International Journal of Industrial Engineering and Management Science}, volume = {6}, number = {2}, pages = {1-16}, year = {2019}, publisher = {University of Hormozgan}, issn = {2409-1871}, eissn = {}, doi = {}, abstract = {Integration in decision making at different organizational and time levels has important implications for increasing the profitability of organizations. Among the important issues of medium-term decision-making in factories, are production planning problems that seek to determine the quantities of products produced in the medium term and the allocation of corporate resources. Furthermore, at short-term, jobs scheduling and timely delivery of orders is one of the vital decision-making issues in each workshop. In this paper, the production planning and scheduling problem in a factory in the north of Iran is considered as a case study. The factory produces cans and bins in different types with ten production lines. Therefore, a mixed integer linear programming (MILP) model is presented for the integrated production planning and scheduling problem to maximize profit. The proposed model is implemented in the GAMS software with the collected data from the real environment, and the optimal scheduling and production planning for the system is presented.}, keywords = {Production Planning,scheduling,mixed integer linear programming}, url = {https://www.ijiems.com/article_90009.html}, eprint = {https://www.ijiems.com/article_90009_049624f60ccfc5d0e7d54c836bbaeb31.pdf} } @article { author = {Seyfi Sariqaya, Mehdi and Chaharsooghi, Seyed Kamal and Husseinzadeh Kashan, Ali and Rahimnezhad, Farideh}, title = {Multi-mode capital-constrained project payment scheduling problem with Discounted Cash Flows}, journal = {International Journal of Industrial Engineering and Management Science}, volume = {6}, number = {2}, pages = {17-36}, year = {2019}, publisher = {University of Hormozgan}, issn = {2409-1871}, eissn = {}, doi = {}, abstract = {Project scheduling is to determine the start time of each project activity, due to the constraints contained in it then determine a timing sequence to perform a series of related activities according to their precedence. So that there is a balance between time completion and total cost of the project and it is to achieve one or more objectives. To achieve these objectives, the options examined and finally, the best option is selected. Despite numerous research on schedule projects, there is lacking in the area of project scheduling with considering financial goals that these problems can be relieved with a good estimation of the costs and expected income. Therefore, in this study, we intend to develop a model for scheduling project performance purposes, including time, cost and financial (income, payment, etc.) with the aim of maximizing profits by right setting of the resources and activities and creating of the optimum cash flow program to prevent financial failure of the project. Where the resources used to implement activities and project incomes represent negative and positive cash flow respectively. As well as various financial factors such as interest rates, payment terms and credit limits not only effect on the cash flow of the project, but the amount and timing of resources affects too.}, keywords = {scheduling,Multi-mode Problem,Genetic Algorithm,Capital-Constrained,Discounted Cash Flows}, url = {https://www.ijiems.com/article_90010.html}, eprint = {https://www.ijiems.com/article_90010_9629322761a338ed3d999c5d373a1f83.pdf} } @article { author = {Sadeghi, Heibatolah}, title = {Optimal pricing and replenishment policy for production system with discrete demand}, journal = {International Journal of Industrial Engineering and Management Science}, volume = {6}, number = {2}, pages = {37-50}, year = {2019}, publisher = {University of Hormozgan}, issn = {2409-1871}, eissn = {}, doi = {}, abstract = {In the classical inventory models, it is assumed that the demand for production items is continue, however, there are various types of manufactured products that demand for their items is discrete and periodic. In this paper, an inventory control model for production systems is developed with discrete demand and interval time between two sequential demand is same. Also, assumed the demand is dependent to the price which demand decreases linearly with the increase in price. We suggest A mixed integer mathematical model and the purpose of this model is maximizing the profit by determining the optimal selling price and replenishment quantity. Mathematical theorems are developed to determine the optimal selling price and replenishment quantity for continue decision variable and then we purposed an algorithm for finding optimal discrete value for the number of periods of demand at the production time and optimal price selling. A numerical example is given to illustrate the theory.}, keywords = {Discrete Demand,Pricing, economic production quantity,optimization}, url = {https://www.ijiems.com/article_90011.html}, eprint = {https://www.ijiems.com/article_90011_63a1fe23f9c716c87cdb1a92aea31d77.pdf} } @article { author = {Abbaspour, Akbar}, title = {Supply chain analysis and improvement by using the SCOR model and Fuzzy AHP: A Case Study}, journal = {International Journal of Industrial Engineering and Management Science}, volume = {6}, number = {2}, pages = {51-73}, year = {2019}, publisher = {University of Hormozgan}, issn = {2409-1871}, eissn = {}, doi = {}, abstract = {Due to the growing competition in supply chains, continuous updates of the supply chain structure are necessary for companies' durability and competitiveness. Therefore, Successful companies, regardless of their current position, are constantly striving to improve and upgrade their supply chain. A lot of research has been conducted so far to achieve the above goals. Hence, the present study aimed to use an appropriate method based on the standard framework of criteria and processes to improve the supply chain capabilities. this standard framework is the supply chain operations reference model(SCOR). Along with this, Fuzzy AHP has been used for valuation plans. The plans provided based on the best practices of the SCOR model. After analyzing the processes and mapping existing supply chain, the pairwise comparisons data obtained from the questionnaire that was completed by the expert of this field, by the use of Fuzzy AHP technique and based on the criteria of the SCOR model, the plan with the maximum weight, was selected and according to it, changes were made in the supply chain.}, keywords = {Analysis,improvement,Supply chain,SCOR,fuzzy AHP}, url = {https://www.ijiems.com/article_90012.html}, eprint = {https://www.ijiems.com/article_90012_7c72e5d3f83b15827e9a6615287d2c40.pdf} } @article { author = {Jafarzadeh Ghoushchi, Saeid and Khazaeili, Mohammad and Sabri-Laghaie, Kamyar}, title = {An extended Multi-Criteria Green Supplier Selection based on Z-Numbers for Fuzzy Multi-Objective Linear Programming Problem}, journal = {International Journal of Industrial Engineering and Management Science}, volume = {6}, number = {2}, pages = {74-96}, year = {2019}, publisher = {University of Hormozgan}, issn = {2409-1871}, eissn = {}, doi = {}, abstract = {The green supplier selection (GSS) problem is a strong and important strategy for companies and organizations that are particularly focused on the environment and technology. This study aims to select the best supplier to optimize order allocation by considering criteria, capacities, and demand. In this study, linguistics variables are firstly used in the form of Z-Numbers to evaluate the weight of criteria. After that, the weights of criteria are obtained by similar to the Z-TOPSIS Method. Thereafter, to select and determine each supplier's order values a Fuzzy multi-objective linear programming (FMOLP) problem is then presented. The proposed model adapts well to even the most complicated membership functions. Finally, the model is further developed using a numerical example at the end of this research. The results of this paper can be implemented in other multi-objective optimization problems, in which the terms uncertainty and reliability of the values of criteria are important.}, keywords = {Multi-criteria decision making,Z-Numbers,Z-TOPSIS,green supplier selection,weighted max-min model}, url = {https://www.ijiems.com/article_90013.html}, eprint = {https://www.ijiems.com/article_90013_d15d1150288ba560ec7ad71d5bcb03af.pdf} } @article { author = {}, title = {Prognostics and Health Management in Machinery: A Review of Methodologies for RUL prediction and Roadmap}, journal = {International Journal of Industrial Engineering and Management Science}, volume = {6}, number = {2}, pages = {97-120}, year = {2019}, publisher = {University of Hormozgan}, issn = {2409-1871}, eissn = {}, doi = {}, abstract = {By the advent of maintenance science, Prognostics and Health Management has gradually penetrated into all the domains of engineering equipment. Machinery prognostics is one of the major tasks in condition based maintenance (CBM), which aims to predict the remaining useful life (RUL) of machinery based on condition information. Costly repairing strategies and Preventive Maintenance are increasingly replaced by modern strategies such as PHM. This strategy, generally, consists of functional modules: data acquisition, data processing, feature extraction/selection, health assessment, diagnosis and prognosis. Although many different methods have been developed in the literature and implemented in different applications for each of the above modules, there is still a need for a comprehensive approach in this matter. This paper attempts to review recent studies in diagnosis and prognostics, as well as data-driven, model-based and hybrid approaches. Finally, the paper provides discussions on current situation of PHM and a roadmap for future trends for researchers in this field is presented.}, keywords = {Prognostics and Health Management,model-based approaches,data-driven approaches,Remaining useful life,Condition Based Maintenance}, url = {https://www.ijiems.com/article_92704.html}, eprint = {https://www.ijiems.com/article_92704_5bdaf763ef6d324688d825fd5d232e83.pdf} }