2024-03-28T13:26:52Z
https://aie.ut.ac.ir/?_action=export&rf=summon&issue=9720
Advances in Industrial Engineering
J. Ind. Eng.
2019
53
1
Identification of the change point in panel data using simultaneously EWMAA and CUSUM
Karim
Atashgar
Naser
Rafiee
Identification of the change point in panel data leads practitioners to focus on the time when really a change takes place in the cross sectional data. Identification of the time helps one to provide a more realistic analysis of the change manifested itself to the process. Different methods of change point identification have been proposed in literature, however, the literature addressees that the sensitivity of identifying the change point is an important issue. This paper attempts to propose a new method with high sensitivity for identifying the change point in a panel data (with large dimension) through a hybrid approach. The proposed method is named Double CUSUM-EWMA. The comparative report addresses that the performance of the proposed method has relatively better performance compared to the existing methods in the literature. This study analyzes several simulated numerical examples with large dimension of panel data when a step shift manifests itself to the process.
Panel data
Change point
Double CUSUM
EWMA
2019
01
01
471
481
https://aie.ut.ac.ir/article_74017_1570dca21edec8618c8637a5f8cf65e8.pdf
Advances in Industrial Engineering
J. Ind. Eng.
2019
53
1
Evapotranspiration monthly using fuzzy neural network model and multiple regression model and comparing the results with real data of FAO Penman Monteith
Nohammad
Ehsanifar
Reza
Ehtesham Rasi
In recent decades, due to the importance of the water issue and increased tendency to calculate the amount of runoff from precipitation, development and implementation of appropriate methods for predicting the precipitation of the data has become essential issue. Knowledge of evapotranspiration and crop water, forms the basis for a proper planning of irrigation-up. Without knowing the amount of water that the plants are or less of the water requirements of plants and reduce yields and cause other problems in agriculture or more of the required amount of plant and waste water and drainage issues such as drain.One of the most important ways to improve the management of water use, especially in agriculture, the major share of water consumption in the country. Precise estimates of water use, which directly depends on the "ET " in plants. The evapotranspiration due to the application of proper management is inevitable water resources. There are many ways to predict evapotranspiration of the reference can be cited methods FAO Penman-Monteith method. Several research is in this field within the country that most of these predictions have been based on empirical methods and new methods have been used less. This research aims to predict the results of the two methods using artificial neural networks and regression trees to predict paid evapotranspiration and as well as to assess the effectiveness of its common Forecast.
Prediction evapotranspiration
Fuzzy Network
Regression tree
Water management
2019
01
01
483
494
https://aie.ut.ac.ir/article_74018_d5db98df701cee972e1f5bab773dde23.pdf
Advances in Industrial Engineering
J. Ind. Eng.
2019
53
1
Unrelated parallel machine scheduling with processing constraints and sequence dependent setup times
Fardin
Ahmadizar
Kasra
Mahdavi
Jamal
Arkat
In real-world problems, machines are often not available for some periods of time due to events such as breakdowns, maintenance activities, and already planned operations. In this research, an unrelated parallel machine scheduling problem is considered where each machine is not available for some times during the planning horizon and also may not be capable of processing some jobs; these constraints are referred to as the processing constraints. On the other hand, the setup times are assumed to be job sequence-dependent as well as machine-dependent. The objective function of the problem considered is to minimize the total earliness and tardiness. First, the problem is formulated as a mixed integer linear programming model and then, in view of its NP-hardness, an imperialist competitive algorithm utilizing a new decoding procedure is proposed to solve large-sized problem instances. To assess the performance of the proposed algorithm, a number of instances are generated and solved.
Scheduling
Unrelated parallel machines
Processing constraints
Sequence-dependent setup
Imperialists competitive algorithm
2019
01
01
495
507
https://aie.ut.ac.ir/article_74019_571889523953d457b66c690107c3db10.pdf
Advances in Industrial Engineering
J. Ind. Eng.
2019
53
1
Modelling the estimation of the optimum number of required equipment and manpower for operational processes under uncertainty conditions (case study: Textile industry)
Bakhtiar
Ostadi
Abolfazl
Ghorbani
Reza
Mokhtarian
The cost of design and building industrial systems is greatly affected by determining the exact number of machineries and human resources, consequently allowing to achieve a higher level of efficiency and productivity. Different methods have been presented to estimate the number of required resources for operational processes. The reliability of the results from these methods is highly dependent on the estimation of the input data which, under uncertain conditions, might have a vague nature and convey incorrect information. Therefore, this study aimed to propose a novel framework based on the fuzzy logic to determine the optimal number of machineries and human resources. The fuzzy set theory was used to determine the percentage of wastes and the time required to complete operational processes. Moreover, to prove the practicality of the proposed model and given the significance of improving the productivity of Textile industry in Iran, the proposed model was employed in a case study of the textile industry and the results were compared with the standard method. The results suggest a significant difference between the number of machineries and human resources estimated by the proposed method and that by the standard method. These differences may negatively affect the performance and optimal usage of the available capacity. The results obtained from the proposed model offer more accurate and comprehensive information under uncertain conditions, allowing us to make appropriate decisions to revise the unused capacity, reduce the cost of idle resources, and increase the efficiency and productivity of the industry.
Number of required equipment
Textile industry
Fuzzy logic
Uncertainty
2019
01
01
509
521
https://aie.ut.ac.ir/article_74020_7726fac97f86b94ad04a1a73ad61d9dd.pdf
Advances in Industrial Engineering
J. Ind. Eng.
2019
53
1
Modeling the abusive of some doctors of patient trust using Markov chain and ZD strategy
Ali
Bahraini
Madjid
Eshaghi Gorji
Ali
Ghaffari
In the present study, the abusive of some doctors from trusting a patient to earn the more financial benefits is investigated using the Markov chain and Zero-Determinant (ZD) strategy. When someone gets sick and visits a doctor, it is clear that the patient should trust the doctor and considers medical advices certainly. The doctors who abuse the trust of patients, they usually use tricks (including scare the patient from getting worse of disease, performing unnecessary tests and performing unnecessary surgery) to prolong the course of the patient's treatment especially for acute diseases. In order to model this problem, the ZD strategy is used for Repetitive games. This strategy helps the doctors to unilaterally consider the probable outcome of opponent (patient) with the desired amount, or to apply a linear relationship between doctor and opponent's consequences. According to the results of the game between the doctor and the patient, it can be concluded that when the doctor’s recommendations aren’t effective for the patient, the patient must go to another doctor to obtain the correct treatment
"Game theory"
" Markov chain"
"Zero-Determinant (ZD) strategy"
2019
01
01
523
528
https://aie.ut.ac.ir/article_74021_74ef5b69d9a37aee7b5c0103fdda7195.pdf
Advances in Industrial Engineering
J. Ind. Eng.
2019
53
1
An mathematical model for surgery scheduling with considering Intensive Care Unit capacity constraint and multiple treatment routes
Meysam
Jafari Eskandari
Roozbeh
Azizmohammadi
Nilofar
Samadi
Scheduling and sequencing operations, as a decision making process, plays an integral role in most manufacturing and producing systems as well as most services environments. Scheduling is especially important in the field of healthcare. The proper scheduling of health wards in a hospital can lead to the optimum use of resources and reduce the cost of staff, overtimes of surgeons, nurses, anesthesiologists and so forth. Along with these achievements, the proper scheduling with the reduction of the waiting time of patients for the reception of services and accelerating the provision of services to emergency patients can upgrade the level of service provision. In this research, the problem of planning and scheduling of the operating room in the heart surgery department is examined. This scheduling is done due to the capacity constraint of the intensive care unit. A very important point in this study is that there are multiple treatment routes for treating patients. In this study first, the pathway for treating patients is estimated by a multinomial logistic regression model. Then the planning and scheduling of patients is done using a mixed integer mathematical model. The goal of this scheduling is to minimize the total treatment time, length of stay and waiting time of patients. In order to measure the effectiveness of the proposed models, the data and processes of the heart center of Tehran have been used.
Surgery Scheduling
Length of Stay
waiting time
Intensive Care Unit
Multiple Treatment Routes
2019
01
01
529
545
https://aie.ut.ac.ir/article_74022_60b8c9d6dcc90aec1aa4c28aa8a9736c.pdf
Advances in Industrial Engineering
J. Ind. Eng.
2019
53
1
Multi-cycle and multi-product Integrated and two objectives model for Production Planning and maintenance considering storage capacity limitations and minimizing the work force changes approach
Mohammad Hasan
Hosseini
Milad
Kolagar Daronkola
Hossein
Amoozad
The problem of production planning and Maintenance is one of the most important decision in production industries and because of their interaction, it is necessary to be studied simultaneously. These two problems are sometimes studied separately that causes to lose ideal result. In this study, a two objectives model is presented for the problem of multi-cycle and multi-product Integrated Production Planning considering storage capacity limitations and Repair and Maintenance. The first objective is minimizing total cost elements that is a known objective in this field, and the second is minimizing work force changes. Although usually the cost of work force changes is considered as an element in total cost, but for some important factors such as social impact, continuous loss of knowledge and skills, and so on it is necessary to considered work force changes as an independent objective. So, at first problem definition via objective functions, parameters, and decision variables are presented. Then mathematical model in multi objective is developed. Since, this problem has been proved as NP-Hard, two approximation methods are also developed based on Non-dominated Sorting Genetic Algorithm II (NSGA-II) and Multi-Objective Imperialism Competitive Algorithm (MOICA). Finally in order to analyze result, this problem is solved with standard data obtained from references. The result show good performance of MOICA in comparison to NSGA-II. However time solution of NSGA-II is better than MOICA.
integrated production planning
maintenance
work force changes
metaheuristic algorithm of NSGA-II
metaheuristic algorithm of MOICA
2019
01
01
547
559
https://aie.ut.ac.ir/article_74023_bd316b14ae650d5e842baac01522bb30.pdf
Advances in Industrial Engineering
J. Ind. Eng.
2019
53
1
Modeling the diffusion of dexterity among workers in the multi-skilled resource-constrained project scheduling problem
Amir Hossein
Hosseinian
Vahid
Baradaran
This paper proposes a new mixed-integer mathematical formulation for the multi-objective multi-skilled resource-constrained project scheduling problem. The objectives of the proposed model are to minimize the make-span and cost of project, simultaneously. In this problem, the workforces can cooperate with each other in working groups to carry out required skills of activities. In the proposed model, workforces have different efficiencies in performing each of their skills and they can improve their efficiencies by learning from more efficient co-workers. Instructing relations between workers have been presented as multiple directed and weighted networks. The problem is NP-hard in the strong sense. Therefore, four multi-objective meta-heuristics have been developed to solve the problem. The performances of algorithms have been compared to each other in terms of convergence, diversity of solutions and computation time. The results show that each of the algorithms has been more successful in providing better results in terms of some performance measures.
Project scheduling problem
Multi-objective optimization
Diffusion of dexterity
Learning phenomenon
2019
01
01
561
573
https://aie.ut.ac.ir/article_74024_81601af910b2c2bdb1fa39b84a58753e.pdf