ORIGINAL_ARTICLE
Gravitational search algorithm for step fixed charge transportation problems
Step fixed-charge transportation problem is an extended version of the fixed charge transportation problem, is one of the most important problems in transportation research area. To tackle such an NP-hard problem, we present Gravitational Search Algorithm (GSA). We solve the randomly generated problems by GSA and also with Genetic Algorithm (GA) to compare them. The obtained results show the proficiency of GSA comparison with GA.
http://aotp.fabad-ihe.ac.ir/article_89552_e641630387157fd3ba11bdf296649cf8.pdf
2019-04-01
1
9
10.22121/aotp.2019.172309.1018
Step fixed-charge transportation problem
NP-hard problem
Gravitational Search Algorithm
Genetic Algorithm
Rohollah
Taghaodi
taghaode@yahoo.com
1
Department of Mathematics, Kashan Branch, Islamic Azad University, Kashan, Iran
LEAD_AUTHOR
Altassan, Kh, El-Sherbiny, M.M., Bokkasam, S. (2012). In handling the step fixed charge transportation problem (ICDeM2012), Kedah, Malaysia, March 15–18.
1
Balinski, M. L. (1961). Fixed cost transportation problems. Naval Research Logistic Quarterly, 8(1): 41–54.
2
Baranifar, S. (2018). A credibility-constrained programming for closed-loop supply chain network design problem under uncertainty. Annals of Optimization Theory and Practice, 1(1), 69-83.
3
El-Sherbiny, M. M. (2012). Alternate mutation based artificial immune algorithm for step fixed charge transportation problem, Egyptian Informatics Journal, 13 (2), 123–134.
4
Kowalski, K., Lev, B. (2008). On step fixed-charge transportation problem, OMEGA, 36(5):913-917.
5
Mahmoodirad, A., Hassasi, H., Tohidi, Gh, Sanei, M., Molla-Alizadeh-Zavardehi, S. (2013). Step Fixed Charge Transportation Problems with Fuzzy Numbers, Scientific Journal of Mechanical and Industrial Engineering, 2(3), 50-56.
6
Mahmoodirad, A., Sanei, M. (2016). Solving a multi-stage multi-product solid supply chain network design problem by meta-heuristics. Scientia Iranica, 23 (3), 1429-1440.
7
Molla-Alizadeh-Zavardehi S., Hajiaghaei-Keshteli, M., Tavakkoli-moghaddam, R. (2011). Solving a capacitated fixed-charge transportation problem by artificial immune and genetic algorithms with a Prüfer number representation, Expert Systems with Applications, 38, 10462–10474.
8
Molla-Alizadeh-Zavardehi, S., Sanei, M., Soltani, R., Mahmoodirad., A. (2014). Solving a step fixed charge transporation problem by a spanning tree-based memetic algorithm, International Journal of Mathematical Modelling & Computations, 4 (2), 181-191.
9
Molla-Alizadeh-Zavardehi, S., Mahmoodirad, A., Rahimian, M. (2014). Step Fixed Charge Transportation Problems via Genetic Algorithm, Indian Journal of Science and Technology, 7 (7), 949-954.
10
Mosallaeipour, S., Mahmoodirad, A., Niroomand,S., Vizvari, B. (2018). Simultaneous selection of material and supplier under uncertainty in carton box industries: a fuzzy possibilistic multi-criteria approach. Soft computing, 22 (9), 2891–2905.
11
Rajabi, F., Najafi, S., Hajiaghaei-Keshteli, M., Molla-Alizadeh-Zavardehi, S. (2013). Solving fuzzy step fixed charge transportation problems via metaheuristics, International Journal of Research in Industrial Engineering, 2, 24-34.
12
Rashedi, E., Nezamabadi-pour, H., Saryazdi, S. (2009). GSA: a gravitational search algorithm, Information Sciences, 179 (13), 2232-2248.
13
Sanei, M., Hassasi, H., Mahmoodirad, A., Rahimian, M. (2014). Fixed-Charge Transportation Problem with Fuzzy Costs, Journal of Applied Science and Agriculture, 9 (9), 1-8.
14
Taghaodi, R., Kardani, F. (2018). Linear programming problem with generalized interval-valued fuzzy numbers. Annals of Optimization Theory and Practice, 1(2), 1-9.
15
ORIGINAL_ARTICLE
Numerical study of a mathematical model of disease caused by water pollution
In Typhoid fever is one of the most common diseases caused by food and water pollution and one of the environmental problems currently in the industrialized world. The infectious disease, like other diseases, including AIDS, hepatitis, etc., is modeled as a nonlinear differential equation system. In this paper, a matrix-Galerkin method is introduced for the numerical study of the mathematical model of Typhoid fever. This method in based on matrix-algabraic computation of Galerkin method that converts the model to algebraic equations. The main purpose is to find an approximate solution with a simple algorithm to determine the population behavior in the Typhoid model. The results of the method show the accuracy and efficiency of the method.
http://aotp.fabad-ihe.ac.ir/article_92100_df974a3b3e8284a882f6a1b6b5517aa2.pdf
2019-04-01
11
18
10.22121/aotp.2019.184438.1019
Matrix-Galerkin method
Typhoid model
Convergence analysis
Hamide
Davtalab
hamide_davtalab@yahoo.com
1
Department of Mathematics, Kharazmi University. Tehran, Iran
AUTHOR
Hojjat Allah
Ebadizadeh
ebadizadeh.h@gmail.com
2
Department of Basic Sciences, Imam Ali University, Tehran, Iran
LEAD_AUTHOR
Simmons, G. (1972). Differential equations with applications and historical notes. New York.
1
Cvjetanović, B., Grab, B., & Uemura, K. (2014). Epidemiological model of typhoid fever and its use in the planning and evaluation of antityphoid immunization and sanitation programmes. Bulletin of the World Health Organization, 45(1), 53.
2
Hyman, J. M. (2006). Differential susceptibility and infectivity epidemic models. Mathematical Biosciences and Engineering, 3, 88-100.
3
Gottlieb, D., & Orszag, S. A. (1977). Numerical analysis of spectral methods: theory and applications (Vol. 26). Siam.
4
Moatlhodl, K., & Gosaamang, K. R. (2017). Mathematical Analysis of Typhoid Infection with Treatment. Journal of Mathematical Sciences: Advances and Applications, 40, 75-91
5
ORIGINAL_ARTICLE
Measuring efficiency in DEA by differential evolution algorithm
In Data Envelopment Analysis (DEA) models, for measuring the relative efficiency of Decision Making Units (DMUs), for a large dataset with many inputs/outputs would need to have a long time with a huge computer. This paper proposed and developed the Differential evolution (DE) for DEA. DE requirements for computer memory and CPU time are far less than that needed by conventional DEA methods and can therefore be a useful tool in measuring the efficiency of large datasets. Since the operators have important roles on the fitness of the algorithms, all the operators and parameters are calibrated by means of the Taguchi experimental design in order to improve their performances.
http://aotp.fabad-ihe.ac.ir/article_92101_d02109bdea5f4a3419c724c0b2c74997.pdf
2019-04-01
19
26
10.22121/aotp.2019.191553.1020
Data Envelopment Analysis
Differential evolution
Taguchi Experimental Design
Mohammad
Rahimian
rahimian.mohammad@gmail.com
1
Department of Mathematics, Masjed-Soleiman Branch, Islamic Azad University, Masjed-Soleiman, Iran
LEAD_AUTHOR
Storn, R., & Price, K. (1997). Differential evolution–a simple and efficient heuristic for global optimization over continuous spaces. Journal of global optimization, 11(4), 341-359.
1
Azadeh, A., Asadzadeh, S. M., & Ahmadi Movaghar, S. (2011). Implementation of data envelopment analysis–genetic algorithm for improved performance assessment of transmission units in power industry. International Journal of Industrial and Systems Engineering, 8(1), 83-103.
2
Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European journal of operational research, 2(6), 429-444.
3
Cooper, W. W., Seiford, L. M., & Tone, K. (2006). Introduction to data envelopment analysis and its uses: with DEA-solver software and references. Springer Science & Business Media.
4
Emrouznejad, A., & Shale, E. (2009). A combined neural network and DEA for measuring efficiency of large scale datasets. Computers & Industrial Engineering, 56(1), 249-254.
5
Udhayakumar, A., Charles, V., & Kumar, M. (2011). Stochastic simulation based genetic algorithm for chance constrained data envelopment analysis problems. Omega, 39(4), 387-397.
6
Thompson, R. G., & Thrall, R. M. (1994). Polyhedral assurance regions with linked constraints. In New Directions in Computational Economics (pp. 121-133). Springer, Dordrecht.
7
Mahmoodirad, A., & Sanei, M. (2016). Solving a multi-stage multi-product solid supply chain network design problem by meta-heuristics. Scientia Iranica E, 23(3), 1428-1440.
8
Molla, a. z. a., Sanei, M., Soltani, R., & Mahmoodirad, A. (2014). Solving a step fixed charge transportation problem by a spanning tree-based memetic algorithm.
9
ORIGINAL_ARTICLE
A strategic approach for improving iron mines in Iran based on a hybrid method
Iron mines are already a sizable segment of the Iranian economy, but it has huge potential for development and can be the driver of further growth. This paper presents a strategic approach with hybrid Grey Relational Analysis (GRA) and Interpretive Structural Modeling (ISM) methodology for improving iron mines in Iran. At first these studies are established strategies and after that presented hybrid GRA and ISM analyses. The result shows the strategic of priorities improvement iron mines are arranged in four levels in Iran: First, an innovative mining and minerals industry with an excellent knowledge base, second, dialogue and cooperation to promote innovation and growth, third, Framework conditions and infrastructure for competitiveness and growth, forth level, a mining and minerals industry in harmony with the environment, culture and other industries and an internationally renowned, active and attractive mining and minerals industry.
http://aotp.fabad-ihe.ac.ir/article_92102_dee03f5ac38468e0d012eb9337d1881c.pdf
2019-04-01
27
39
10.22121/aotp.2019.92102
strategy
Mining
hybrid approach
Saeid
Ghane
ghane_saeed@yahoo.com
1
Department of Industrial Engineering, Masjed-Soleiman Branch, Islamic Azad University, Masjed-Soleiman, Iran
LEAD_AUTHOR
https://www.economist.com/finance-and-economics/2012/10/13/the-lore-of-ore
1
"Mining in Iran – CountryMine". InfoMine. Retrieved 18 October 2011.
2
Jump up to:a b "Archived copy". Archived from the original on 24 November 2011. Retrieved 28 November 2011.
3
"Archived copy". Archived from the original on 21 October 2008. Retrieved 2010-03-15.
4
http://www.earthstonegroup.com/blog/?p=709
5
Shiau, T. A., & Hsu, C. Y. (2003, October). APPLICATION OF GRA AND ISM INTEGRATION MODEL FOR THE EVALUATION OF INTERNATIONAL PORT LOGISTICS STRATEGIES. In Proceedings of the Eastern Asia Society for Transportation Studies (Vol. 4).
6
http://www.adlittle.com/sites/default/files/viewpoints/adl_iranian_metals_mining_industry-web.pdf
7
http://www.iran-daily.com/News/216078.html
8
https://financialtribune.com/articles/economy-business-and-markets/80205/iran-sixth-largest-iron-ore-exporter-to-china
9
"Archived copy" (PDF). Archived from the original (PDF) on 28 September 2011. Retrieved 15 March 2010.
10
"Iran world's 8th iron ore producer: report". Tehran Times. Retrieved 18 October 2011.
11
"Molybdenum Production by Country (Metric tons of contained molybdenum)". Indexmundi.com. Retrieved 18 October 2011.
12
"Steel Production Capacity at 20m Tons". Zawya. 23 September 2010. Archived from the original on 5 January 2013. Retrieved 18 October 2011.
13
IRNA:Iran: $30 Billion Dollar to be invested in industry. Retrieved 15 November 2008.
14
Kung, C. Y., & Wen, K. L. (2007). Applying grey relational analysis and grey decision-making to evaluate the relationship between company attributes and its financial performance—a case study of venture capital enterprises in Taiwan. Decision Support Systems, 43(3), 842-852.
15
Chen, F. L., & Ou, T. Y. (2009). Gray relation analysis and multilayer functional link network sales forecasting model for perishable food in convenience store. Expert Systems with Applications, 36(3), 7054-7063.
16
Chang, Y. C. (1999). Grey Relational Analysis: The introduction of Grey System theory.
17
Shiau, T. A., & Hsu, C. Y. (2003, October). APPLICATION OF GRA AND ISM INTEGRATION MODEL FOR THE EVALUATION OF INTERNATIONAL PORT LOGISTICS STRATEGIES. In Proceedings of the Eastern Asia Society for Transportation Studies (Vol. 4).
18
Wu, W. Y., Hsiao, S. W., & Tsai, C. H. (2008). Forecasting and evaluating the tourist hotel industry performance in Taiwan based on Grey theory. Tourism and hospitality Research, 8(2), 137-152.
19
Sage, A. P. (1977). Methodology for large-scale systems.
20
Ghodsypour, S. H., & O'Brien, C. (1998). A decision support system for supplier selection using an integrated analytic hierarchy process and linear programming. International journal of production economics, 56, 199-212.
21
Thakkar, J., Deshmukh, S. G., Gupta, A. D., & Shankar, R. (2007). Development of a balanced scorecard. International Journal of Productivity and Performance Management.
22
Mandal, A., & Deshmukh, S. G. (1994). Vendor selection using interpretive structural modelling (ISM). International Journal of Operations & Production Management, 14(6), 52-59.
23
Nadkarni, S., & Shenoy, P. P. (2001). A Bayesian network approach to making inferences in causal maps. European Journal of Operational Research, 128(3), 479-498.
24
Kwahk, K. Y., & Kim, Y. G. (1999). Supporting business process redesign using cognitive maps. Decision Support Systems, 25(2), 155-178.
25