ORIGINAL_ARTICLE
A Batch-wise ATP Procedure in Hybrid Make-to-Order/Make-to-Stock Manufacturing Environment
Satisfying customer demand necessitates manufacturers understanding the importance of Available-To-Promise (ATP). It directly links available resources to customer orders and has significant impact on overall performance of a supply chain. In this paper, an improvement of the batch-mode ATP function in which the partial fulfillment of the orders is available will be proposed. In other words, in a hybrid make-to-order/make-to-stock manufacturing environment, the proposed model responds to customer’s requests in 3 different ways; rejecting, fulfilling, and partial fulfilling. By using this procedure, the reliability of order fulfillment and the responsiveness of order promising will be enhanced. To evaluate the applicability of the proposed model, some numerical examples and sensitivity analysis are conducted. Results show that by applying partial fulfilment and penalty to backorders, the number of rejected orders and profit would be minimized and maximized, respectively.
https://jqepo.shahed.ac.ir/article_676_450d6a193adfc63ef0b8433f0306bd62.pdf
2018-01-01
1
12
10.22070/jqepo.2017.1088.1030
ATP
batch-mode ATP
partial fulfillment
Masoud
Rabbani
mrabani@ut.ac.ir
1
School of Industrial Engineering, College of Engineering, University of Tehran
LEAD_AUTHOR
Amir
Farshbaf-Geranmayeh
afarshbaf@ut.ac.ir
2
School of Industrial and System Engineering, College of Engineering, University of Tehran
AUTHOR
Fereshteh
Vahidi
f.vahidi@ut.ac.ir
3
School of Industrial and System Engineering, College of Engineering, University of Tehran, Iran
AUTHOR
Beemsterboer, B., Land, M., & Teunter, R. (2016). Hybrid MTO-MTS production planning: An explorative study. European Journal of Operational Research, 248(2), 453-461.
1
Chen, C. Y., Zhao, Z. Y., & Ball, M. O. (2001). Quantity and due date quoting available to promise. Information Systems Frontiers, 3(4), 477-488.
2
Cheng, C. B., & Cheng, C. J. (2011). Available-to-promise based bidding decision by fuzzy mathematical programming and genetic algorithm. Computers & Industrial Engineering, 61(4), 993-1002.
3
Cheng, C. B., & Wu, M. T. (2015). Customer Order Fulfillment Based on a Rolling Horizon Available-to-Promise Mechanism: Solution by Fuzzy Approach and Genetic Algorithm. In Intelligent Systems' 2014 (pp. 477-488). Springer International Publishing.
4
Chen-Ritzo, C. H., Ervolina, T., Harrison, T. P., & Gupta, B. (2011). Component rationing for available-to-promise scheduling in configure-to-order systems. European Journal of Operational Research, 211(1), 57-65.
5
Chien-Yu, C., Zhao, Z., & Ball, M. O. (2002). A model for batch advanced available-to-promise. Production and Operations Management, 11(4), 424.
6
Fleischmann, B., Meyr, H., & Wagner, M. (2015). Advanced planning. In Supply chain management and advanced planning (pp. 71-95). Springer Berlin Heidelberg.
7
Lin, J. T., Hong, I. H., Wu, C. H., & Wang, K. S. (2010). A model for batch available-to-promise in order fulfillment processes for TFT-LCD production chains. Computers & Industrial Engineering, 59(4), 720-729.
8
Olhager, J., & Prajogo, D. I. (2012). The impact of manufacturing and supply chain improvement initiatives: A survey comparing make-to-order and make-to-stock firms. Omega, 40(2), 159-165.
9
Pibernik, R. (2002). Ausgewählte Methoden und Verfahren zur Unterstützung des Advanced Available to Promise. Zeitschrift für Planung, 13(4), 345-372.
10
Pibernik, R. (2005). Advanced available-to-promise: Classification, selected methods and requirements for operations and inventory management. International journal of production economics, 93(1), 239-252.
11
Rabbani, M., Monshi, M., & Rafiei, H. (2014). A new AATP model with considering supply chain lead-times and resources and scheduling of the orders in flowshop production systems: A graph-theoretic view. Applied Mathematical Modelling, 38(24), 6098-6107.
12
Rabbani, M., Sadri, S., Manavizadeh, N., & Rafiei, H. (2015). A novel bi-level hierarchy towards available-to-promise in mixed-model assembly line sequencing problems. Engineering Optimization, 47(7), 947-962.
13
Robinson, A. G., & C. Carlson, R. C. (2007). Dynamic order promising: real-time ATP. International journal of integrated supply management, 3(3), 283-301.
14
Slotnick, S. A. (2011). Order acceptance and scheduling: A taxonomy and review. European Journal of Operational Research, 212(1), 1-11.
15
Tinnefeld, C., Krueger, J., Schaffner, J., & Bog, A. (2008). A database engine for flexible real-time available-to-promise. Paper presented at the Advanced Management of Information for Globalized Enterprises, 2008. AMIGE 2008. IEEE Symposium on.
16
Tsai, K. M., & Wang, S. C. (2009). Multi-site available-to-promise modeling for assemble-to-order manufacturing: An illustration on TFT-LCD manufacturing. International journal of production economics, 117(1), 174-184.
17
Xiong, M., Tor, S. B., Khoo, L. P., & Chen, C. H. (2003). A web-enhanced dynamic BOM-based available-to-promise system. International journal of production economics, 84(2), 133-147.
18
Zhao, Z., Ball, M. O., & Kotake, M. (2005). Optimization-based available-to-promise with multi-stage resource availability. Annals of Operations Research, 135(1), 65-85.
19
ORIGINAL_ARTICLE
An Improved Tabu Search Algorithm for Job Shop Scheduling Problem Trough Hybrid Solution Representations
Job shop scheduling problem (JSP) is an attractive field for researchers and production managers since it is a famous problem in many industries and a complex problem for researchers. Due to NP-hardness property of this problem, many meta-heuristics are developed to solve it. Solution representation (solution seed) is an important element for any meta-heuristic algorithm. Therefore, many researchers try to present different encodings to solve this problem. Fattahi et al., and Gen & Cheng suggested two solutions for this problem that both have advantages and weaknesses in searching solution space to reach an acceptable solution. In the current paper, a cyclic algorithm based on tabu search algorithm was proposed to improve the exploration and exploitation powers of these encodings. Also, several problems of different sizes are solved by it and the obtained results were compared. Results showed the applicability and effectiveness of the proposed solution representation in comparison with the existing ones
https://jqepo.shahed.ac.ir/article_677_23d2aa7b8e6067dde458b0e972df2541.pdf
2018-01-01
13
26
10.22070/jqepo.2018.1360.1035
Job Shop Scheduling Problem
Solution Representation
Tabu Search algorithm
Parviz
Fattahi
p.fattahi@alzahra.ac.ir
1
Alzahra University
LEAD_AUTHOR
Masume
Messi Bidgoli
bidgoli_m2000@yahoo.com
2
Bu-Ali Sina University
AUTHOR
Parvaneh
Samouei
samouei_parvaneh@yahoo.com
3
Bu-Ali Sina University
AUTHOR
Asadzadeh, L. (2015). A local search genetic algorithm for the job shop scheduling problem with intelligent agents.Computers & Industrial Engineering, 85, 376–383.
1
Bagheri, A., et al. (2010). "An artificial immune algorithm for the flexible job-shop scheduling problem." Future Generation Computer Systems, 26.4, 533-541.
2
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3
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4
Bülbül, K. (2011). A Hybrid Shifting Bottleneck-Tabu Search Heuristic For The Job Shop Total Weighted Tardiness Problem. Computers & Operations Research, 38, 967-983.
5
Chang, P., Lin, K., Pai, P., Zhong, C., Lin, C., & Hung, L. (2008). Ant Colony Optimization System For A Multi-Quantitative And Qualitative Objective Job-Shop Parallel-Machine-Scheduling Problem.International Journal of Production Research, 46(20), 5719-5759.
6
Cheng, R., Gen, M., & Tsujimura, Y. (1996). A Tutorial Survey of Job-Shop Scheduling Problems Using Genetic Algorithms-I Representation”, Computers & Industrial Engineering, 30, 983-997.
7
Dauzere-Peres S Paulli J. (1997). An integrated approach for modeling and solving the general multiprocessor job shop scheduling problem using tabu search, Ann. Operat. Res, 70, 281–306.
8
De Giovanni, L., & Ferdinando P. (2010). "An improved genetic algorithm for the distributed and flexible job-shop scheduling problem." European journal of operational research, 200.2, 395-408.
9
Elmi, A., Solimanpur, M., Topaloglu, S., & Elmi, A. (2011). "A Simulated Annealing Algorithm For The Job Shop Cell Scheduling Problem With Intercellular Moves And Re-entrant Parts", Computers & Industrial Engineering, 61, 171-178.
10
Fattahi P, Saidi M & Jolai F. (2007). Mathematical modeling and heuristic approaches to flexible job shop scheduling problems. J Intell Manuf, 18:331–342
11
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12
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13
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15
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22
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23
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24
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25
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27
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28
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29
Rabiee, M.,Zandieh, M., & Ramezani. P. (2012). Bi-Objective Partial Flexible Job Shop Scheduling Problem: NSGA-II, NRGA, MOGA And PAES Approaches. International Journal of Production Research, 50(24), 7327-7342.
30
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31
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32
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33
Zhao, F., Zhang, J., Zhang, C., & Wang, J. (2015). An improved shuffled complex evolution algorithm with sequence mapping mechanism for job shop scheduling problems. Expert Systems with Applications, 42 (8), 3953–3966.
34
ORIGINAL_ARTICLE
Systems Risk Analysis UsingHierarchical Modeling
A fresh look at the system analysis helped us in finding a new way of calculating the risks associated with the system. The author found that, due to the shortcomings of RPN, more researches needed to be done in this area to use RPNs as a new source of information for system risk analysis. It is the purpose of this article to investigate the fundamental concepts of failure modes and effects analysis to propose a conceptual hierarchically based model for calculating the risk associated with a system in general. To do so, the author developed a chance constrained goal programming model for solving the problem. A sample problem is provided to show the calculation process of risk evaluation. The findings of this article can be used for calculating the level of risk associated with the entire system provided that the RPN of each unit of subsystems is known beforehand. This model helps the managers to calculate the system risk from the perspective of management, because it is a computer aided decision making (CADM) tool
https://jqepo.shahed.ac.ir/article_678_3c362db97c8a855b704c1b8ae86dfb3f.pdf
2018-01-01
27
42
10.22070/jqepo.2018.908.1028
Failure Modes and Effects Analysis
CADM
Goal Programming
Chance Constrained Programming
RPN
Risk
System Risk Calculations
yahia
zare mehrjerdi
mehrjerdyazd@gmail.com
1
Department of Industrial engineering, Yazd University
LEAD_AUTHOR
Ahsen, A. V. (2008). Cost-oriented failure mode and effects analysis. International Journal of Quality & Reliability Management, 25, 466-476.
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77
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78
ORIGINAL_ARTICLE
A Multi-Criteria Analysis Model under an Interval Type-2 Fuzzy Environment with an Application to Production Project Decision Problems
Using Multi-Criteria Decision-Making (MCDM) to solve complicated decisions often includes uncertainty, which could be tackled by utilizing the fuzzy sets theory. Type-2 fuzzy sets consider more uncertainty than type-1 fuzzy sets. These fuzzy sets provide more degrees of freedom to illustrate the uncertainty and fuzziness in real-world production projects. In this paper, a new multi-criteria analysis model is introduced based on new compromise ratio and relative preference relation methods by vicinity to positive ideal and distance from negative ideal concepts under an interval type-2 fuzzy environment. Also, qualitative criteria are expressed as linguistic variables. Relative preference relation is more reasonable than defuzzification, because defuzzification cannot provide preference degree between two fuzzy numbers and cannot keep all the information. In this paper, an extended relative preference relation over the average is presented to deal with numeral values. Finally, a real application to designing and manufacturing of small electronic components, particularly for the aviation, defense, and space industries, is adopted from the literature and solved to determine the critical path by considering efficient criteria such as time, cost, risk, and quality.
https://jqepo.shahed.ac.ir/article_679_7fa56664080f849fc1d0f3acf60c094a.pdf
2018-01-01
43
66
10.22070/jqepo.2018.2402.1049
Multi-criteria decision-making (MCDM)
Interval type-2 fuzzy sets (IT2FSs)
Relative preference relation
Compromise ratio method
Production projects
Critical path selection problem
Y.
Dorfeshan
yahyad_147@yahoo.com
1
Shahed University
AUTHOR
S. Meysam
Mousavi
smemusavi@yahoo.com
2
Khalije Fars Highway
LEAD_AUTHOR
Behnam
Vahdani
b.vahdani@gmail.com
3
Islamic Azad University
AUTHOR
Amiri, M., & Golozari, F. (2011). Application of fuzzy multi-attribute decision making in determining the critical path by using time, cost, risk, and quality criteria. International Journal of Advanced Manufacturing Technology, 54(1), 393-401.
1
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34
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35
ORIGINAL_ARTICLE
Applying Grey E-S-QUAL Model to Evaluate the Gaps between Expectation and Perception of the Customer Based on E-services Quality: A Case Study of an Iranian Online Retailer
This study aims to apply Grey system based on modified E-S-Qual model to analyze e-service quality.Questionnaires on the basis of E-S-Qual model, which consisted in 7 dimensions, were distributed among customers of 5040.ir, an online retailer in Iran. 251 questionnaires were obtainedfrom the customer’s website. After applying the method and calculating the scores in each dimension, the gap between expectations and perceptions was calculated. The results show that, among 7 dimensions, there are 4 positive and 3 negative gaps.Accordingly,with the aid of the Importance-Performance Matrix, the results are further analyzed. At the end of this study, some suggestions are made for improving quality of the e-services based on results analysis
https://jqepo.shahed.ac.ir/article_680_78d988116bee48e70a43d8bddcc4abc5.pdf
2018-01-01
67
80
10.22070/jqepo.2018.1931.1042
E-service quality
E-S-QUAL model
Grey numbers
Iran
Seyed hasan
hosseini
sh.hosseini51@gmail.com
1
shahrood university
LEAD_AUTHOR
Mohammad Ehsan
Souri
ehsan.souri1991@gmail.com
2
MSc Student of MBA, Shahrood university of technology
AUTHOR
Fatemeh
Sajjadian
fatemeh.sajadian2015@gmail.com
3
MSc Student of MBA, Shahrood university of technology
AUTHOR
Abedin, Z. (2015). Service quality level and the perception of customers: a study on Nihgoom tours– a 5* rated travel and tourism compaby in Bangladesh. British Journal of Marketing Studies, 3(3), 80-100.
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3
Chuanmin, M., Xiaofei , S., Yuan, Q., Yosa, S., & Ye, C. (2014). A new method for evaluating tour online review based on grey 2-tuple linguistic. Kybernetes, 43(3/4), 601-613.
4
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5
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7
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8
Hair, J., Black, W., Babin, B., Anderson, R., & Tatham, R. (2006). Multivariate data analysis. NJ: Pearson Education Inc.
9
Ibarra, L., Casas, E., & Partida, A. (2014). Servqual Method Applied to Agencia Fiscal Del Estado De Sonora: An Analysis about Service Quality. Procedia - Social and Behavioral Sciences, 148(25), 87–93.
10
Kamfiroozi, M., Aliahmadi, A., & Jafari Eskandari, M. (2012). Application of Three Parameter Interval Grey Numbers in Enterprise Resource Planning Selection. International Journal of Information, Security and Systems Management, 1(2), 72-77.
11
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Li , Y., Zhu, S., & Guo, S. D. (2016). Multi-attribute grey target decision method with three-parameter interval grey number. Grey Systems: Theory and Application, 6(2), 270-280.
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Su, Q., Li, Z., Song, Y. T., & Chen, T. (2008). Conceptualizing consumers' perceptions of e‐commerce quality. International Journal of Retail & Distribution Management, 5(36), 360-374.
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38
Udo, G. J., Bagchi, K. K., & Kirs, P. J. (2011). Using SERVQUAL to assess the quality of e-learning experience. Computers in Human Behavior, 27(3), 1272–1283.
39
Urdang, B. S., & Howey, R. M. (2001). Assessing damages for non-performance of a travel professional—a suggested use of “servqual”. Tourism Management, 22(5), 533–538.
40
Wei, C., & Jun‐fu, C. (2011). Theoretical discussion of applying grey system theory in neuropsychological studies. Grey Systems: Theory and Application, 1(3), 268-273.
41
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42
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43
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44
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46
Zhang, M., Huang, L., He, Z., & Wang, A. G. (2015). E-service quality perceptions: an empirical analysis of the Chinese. Total Quality Management, 26(11-12), 1357-1372.
47
ORIGINAL_ARTICLE
Preferred Robust Response Surface Design with Missing Observations Based on Integrated TOPSIS-AHP Method
- Missing observations occur in experimental designs as a result of insufficient sampling, machine breakdown, high cost, and errors in the measurements. In nanomanufacturing, missing observations often appear in designs because the combination of factors or molecular structures selected by a designer cannot be experimented successfully. In the current paper, Box-Behnken and face-centered composite designs were studied and eight robustness criteria including D-efficiency, tmax, tmax( ), and their related sub-criteria were considered to evaluate the robustness of the aforementioned designs. Finally, the integrated TOPSIS-AHP methodology was employed to select the most suitable robust design, and a numerical example was also presented to assess the applicability of the proposed approach
https://jqepo.shahed.ac.ir/article_681_8c4330053cc6192fe3c842aa45bda3b5.pdf
2018-01-01
81
91
10.22070/jqepo.2018.1110.1033
Robustness criteria
Preferred robust response surface design
TOPSIS-AHP methodology
Nanomanufacturing
Atefeh
Ashuri
atefeh.ashuri@gmail.com
1
Industrial Engineering Department, Shahed University, Tehran, Iran
AUTHOR
Mahdi
Bashiri
bashiri.m@gmail.com
2
Industrial Engineering Department, Shahed University, Tehran, Iran
AUTHOR
Amirhossein
Amiri
amirhossein.amiri@gmail.com
3
Industrial Engineering Department, Faculty of Engineering, Shahed University, Tehran, Iran
LEAD_AUTHOR
K. Lal, V.K. Gupa, & L. Bar, (2001). “Robustness of designed experiments against missing data”,Journal of Applied Statistics, 28, 63-79.
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24