Scientia Iranica

Scientia Iranica

Optimizing supply chain network design with location-inventory decisions for perishable items: A Pareto-based MOEA approach

Authors
Sadra Rashidi
Abbas Saghaei
Seyed Jafar Sadjadi
Soheil Sadi-Nezhad
10.24200/sci.2016.4009
Abstract
In this paper, a bi-objective mathematical model is presented to optimize supply chain network with location-inventory decisions for perishable items. The goals are to minimize total cost of system including transportation cost of perishable items from centers into DCs, DCs to ultimate center, transportation cost of unusual orders, and fixed cost of centers as DCs as well as demand unresponsiveness. Considering special conditions for holding items, regional DCs, and determining average of life time items assigned to centers are other features of the proposed model. With regard to complexity of the proposed model, a Pareto-based meta-heuristic approach called multi-objective imperialist competitive algorithm (MOICA) is presented to solve the model. To demonstrate performance of proposed algorithms, two well-developed multi-objective algorithms based on genetic algorithm including non-dominated ranked genetic algorithm (NRGA) and non-dominated sorting genetic algorithm (NSGA-II) are applied. In order to analyze the results, several numerical illustrations are generated; then, the algorithms compared both statistically and graphically. The results analysis show the robustness of MOICA to find and manage Pareto solutions.
Keywords
supply chain network design
Perishable products
location-inventory
multi-objective optimization
Pareto-based meta-heuristics
Scientia Iranica
Volume 23, Issue 6 - Serial Number 6
Transactions on Industrial Engineering (E)
December 2016
Pages 3025-3045

  • Receive Date 10 February 2015
  • Accept Date 27 July 2017