Volume 32, Issue 3 (IJIEPR 2021)                   IJIEPR 2021, 32(3): 1-17 | Back to browse issues page

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Ramezanian R, Jani S. Design a Relief Transportation Model with Uncertain Demand and Shortage Penalty: Solving with Meta-Heuristic Algorithms. IJIEPR 2021; 32 (3) :1-17
URL: http://ijiepr.iust.ac.ir/article-1-818-en.html
Design a Relief Transportation Model with Uncertain Demand and Shortage Penalty: Solving with Meta-Heuristic Algorithms
Reza Ramezanian 1, Soleiman Jani2
1- Department of Industrial Engineering, K. N. Toosi University of Technology , Ramezanian@kntu.ac.ir
2- Department of Industrial Engineering, Payam-Noor-Shemiranat
Abstract:   (2163 Views)
In this paper, a fuzzy multi-objective optimization model in the logistics of relief chain for response phase planning is addressed. The objectives of the model are: minimizing the costs, minimizing unresponsive demand, and maximizing the level of distribution and fair relief. A multi-objective integer programming model is developed to formulate the problem in fuzzy conditions and transformed to the deterministic model using Jime'nez approach. To solve the exact multi-objective model, the ε-constraint method is used. The resolved results for this method have shown that this method is only able to find the solution for problems with very small sizes. Therefore, in order to solve the problems with medium and large sizes, multi-objective cuckoo search optimization algorithm (MOCSOA) is implemented and its results are compared with the NSGA-II. The results showed that MOCSOA in all cases has the higher ability to produce higher quality and higher-dispersion solutions than NSGA-II.
 
Keywords: relief chain, response phase planning, inventory displacement, fair relief, MOCSOA, NSGA-II.
Full-Text [PDF 759 kb]   (761 Downloads)    
Type of Study: Research | Subject: Logistic & Apply Chain
Received: 2018/03/15 | Accepted: 2021/07/19 | Published: 2021/06/9
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