Designing a Strong Distribution Network with Considering Justice in Distributing Products under Fuzzy Uncertainty (Case Study: Tehran Province)

Document Type : Original Article

Authors

Abstract

The design of the distribution network of all livestock units is similar to that provided by the management.
The woman was taken to safety. The design of the meter is designed to be evenly distributed
Different types of snails, especially those suffering from malnutrition, are taken from this
It is clear from the method that this method can be used in such a way that it can not be seen in any way.
He was arrested. In this research, a group of people will be invited to study and study.
The goal is to maximize the total cost, environmental impact and competitiveness of the market.
Social justice can be achieved by limiting the production of goods in the region.
The customer is under consideration.

References

[1] Ouhimmou, M., et al., Design of robust distribution network under demand uncertainty: A case study in the pulp and paper. International Journal of Production Economics. 218 (2019)96-105.
 
[2] Mishra, S. and S.P. Singh, Distribution network model using big data in an international environment. Science of the Total Environment. 707 (2020)135549.
 
[3] Melchor-Pereda, P., et al., Methodology for Storage Location Allocation Based on the Planning of Material Requirements, in Handbook of Research on Developments and Trends in Industrial and Materials Engineering. 2020, IGI Global. p. 50-77.
 
[4] Rahimi, M., V. Ghezavati, and F. Asadi, A stochastic risk-averse sustainable supply chain network design problem with quantity discount considering multiple sources of uncertainty. Computers Industrial Engineering. 130 (2019)430-449.
 
[5] Pettit, T.J., K.L. Croxton, and J. Fiksel, The evolution of resilience in supply chain management: a retrospective on ensuring supply chain resilience. Journal of Business Logistics. 40(1) (2019)56-65.
 
[6] Pishvaee, M.S., M. Rabbani, and S.A. Torabi, A robust optimization approach to closed-loop supply chain network design under uncertainty. Applied Mathematical Modelling. 35(2) (2011)637-649.
 
[7] Govindan, K., M. Fattahi, and E. Keyvanshokooh, Supply chain network design under uncertainty: A comprehensive review and future research directions. European Journal of Operational Research. 263(1) (2017)108-141.
 
[8] Silva, F.J.F. and D. De la Figuera, A capacitated facility location problem with constrained backlogging probabilities. International journal of production research. 45(21) (2007)5117-5134.
 
[9] Klose, A. and A. Drexl, Facility location models for distribution system design. European journal of operational research. 162(1) (2005)4-29.
 
[10] Barreto, S., et al., Using clustering analysis in a capacitated location-routing problem. European Journal of Operational Research. 179(3) (2007)968-977.
 
[11] Prins, C., et al., Solving the capacitated location-routing problem by a cooperative Lagrangean relaxation-granular tabu search heuristic. Transportation Science. 41(4) (2007)470-483.
 
[12] Chen, C.-H. and C.-J. Ting, Combining lagrangian heuristic and ant colony system to solve the single source capacitated facility location problem. Transportation research part E: logistics and transportation review. 44(6) (2008)1099-1122.
 
[13] Lin, C., Stochastic single-source capacitated facility location model with service level requirements. International Journal of Production Economics. 117(2) (2009)439-451.
 
[14] Jafari, A., M. Sharif-Yazdi, and M. Jafarian, A New Multi-objective Approach in Distribution Centers Location Problem in Fuzzy Environment. Journal of uncertain systems. 4(2) (2010)133-146.
 
[15] Vincent, F.Y., et al., A simulated annealing heuristic for the capacitated location routing problem. Computers Industrial Engineering. 58(2) (2010)288-299.
 
[16] Zarandi, M.H.F., A. Hemmati, and S. Davari, The multi-depot capacitated location-routing problem with fuzzy travel times. Expert Systems with Applications. 38(8) (2011)10075-10084.
 
[17] Küçükdeniz, T., et al., Integrated use of fuzzy c-means and convex programming for capacitated multi-facility location problem. Expert Systems with Applications. 39(4) (2012)4306-4314.
 
[18] Contardo, C., J.-F. Cordeau, and B. Gendron, An exact algorithm based on cutand-column generation for the capacitated location-routing problem. INFORMS Journal on Computing. 26(1) (2014)88-102.
 
[19] Nadizadeh, A. and H.H. Nasab, Solving the dynamic capacitated location-routing problem with fuzzy demands by hybrid heuristic algorithm. European Journal of Operational Research. 238(2) (2014)458-470.
 
[20] Rahmani, A. and S. MirHassani, A hybrid firefly-genetic algorithm for the capacitated facility location problem. Information Sciences. 283 (2014)70-78.
 
[21] Diabat, A., A capacitated facility location and inventory management problem with single sourcing. Optimization Letters. 10(7) (2016)1577-1592.
 
[22] Nadizadeh, A. and B. Kafash, Fuzzy capacitated location-routing problem with simultaneous pickup and delivery demands. Transportation Letters. 11(1) (2019)1-19.
 
[23] Zahiri, B., J. Zhuang, and M. Mohammadi, Toward an integrated sustainableresilient supply chain: A pharmaceutical case study. Transportation Research Part E: Logistics and Transportation Review. 103 (2017)109-142.
 
[24] Hong, Y.S., W.T. Huh, and C. Kang, Sourcing assemble-to-order inventories under supplier risk uncertainty. Omega. 66 (2017)1-14.
 
[25] Jabbarzadeh, A., B. Fahimnia, and F. Sabouhi, Resilient and sustainable supply chain design: sustainability analysis under disruption risks. International Journal of Production Research. 56(17) (2018)5945-5968.
 
[26] Zadeh, L.A., Fuzzy sets. Information and control. 8(3) (1965)338-353.
 
[27] Chen, S.H. and C.H. Hsieh, Representation, ranking, distance, and similarity of LR type fuzzy number and application. Australian Journal of Intelligent Processing Systems. 6(4) (2000)217-229.
 
[28] Lootsma, F.A., Saaty’s priority theory and the nomination of a senior professor in operations research. European Journal of Operational Research. 4(6) (1980)380-388.
 
[29] Rezaei, J., Best-worst multi-criteria decision-making method: Some properties and a linear model. Omega. 64 (2016)126-130.
 
[30] Ranjbar, H.R. and M.A. Nekooie, An improved hierarchical fuzzy TOPSIS approach to identify endangered earthquake-induced buildings. Engineering Applications of Artificial Intelligence. 76 (2018)21-39.
 
[31] Kahraman, C., et al., Fuzzy multi-criteria evaluation of industrial robotic systems using TOPSIS, in Fuzzy multi-criteria decision making. 2008, Springer. p. 159-186.
 
[32] Olivares-Benitez, E., R.Z. Ríos-Mercado, and J.L. González-Velarde, A metaheuristic algorithm to solve the selection of transportation channels in supply chain design. International Journal of Production Economics. 145(1) (2013)161-172.
 
[33] Khalili-Damghani, K., M. Nojavan, and M. Tavana, Solving fuzzy Multidimensional Multiple-Choice Knapsack Problems: The multi-start Partial Bound Enumeration method versus the efficient epsilon-constraint method. Applied Soft Computing. 13(4) (2013)1627-1638.
 
[34] Mavrotas, G., Effective implementation of the ε-constraint method in multiobjective mathematical programming problems. Applied mathematics and computation. 213(2) (2009)455-465.
 
[35] Sadjadi, S.J., M. Heidari, and A.A. Esboei, Augmented ε-constraint method in multiobjective staff scheduling problem: a case study. The International Journal of Advanced Manufacturing Technology. 70(5-8) (2014)1505-1514.
 
[36] Sheu, R.-L. and J. Lin, Solving continuous min-max problems by an iterative entropic regularization method. Journal of Optimization Theory and Applications. 121(3) (2004)597-612.
 
[37] Pishvaee, M.S., J. Razmi, and S.A. Torabi, Robust possibilistic programming for socially responsible supply chain network design: A new approach. Fuzzy sets and systems. 206 (2012)1-20.
Fuzzy Systems and its Applications
Volume 4, Issue 1 - Serial Number 7
November 2021
Pages 1-46

Files

History

  • Receive Date: 29 March 2020
  • Revise Date: 22 August 2020
  • Accept Date: 01 February 2021

Share

How to cite

Statistics