TITLE

A Self-Learning Particle Swarm Optimization for Robust Multi-Echelon Capacitated Location–Allocation–Inventory Problem

AUTHOR(S)
Tirkolaee, Erfan Babaee; Mahmoodkhani, Javad; Bourani, Mehdi Ranjbar; Tavakkoli-Moghaddam, Reza
PUB. DATE
December 2019
SOURCE
Journal of Advanced Manufacturing Systems;Dec2019, Vol. 18 Issue 4, p677
SOURCE TYPE
Academic Journal
DOC. TYPE
Article
ABSTRACT
This paper addresses a multi-echelon capacitated location–allocation–inventory problem under uncertainty by providing a robust mixed integer linear programming (MILP) model considering production plants at level one, central warehouses at level two, and the retailers at level three in order to design an optimal supply chain network. In this model, the retailer's demand parameter is uncertain and just its upper and lower bounds within an interval are known. In order to deal with this uncertainty, a robust optimization approach is used. Then, a self-learning particle swarm optimization (SLPSO) algorithm is developed to solve the problem. The results show that the proposed algorithm outperforms the exact method by providing high quality solutions in the reasonable amount of computational runtime.
ACCESSION #
139730330

 

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