In this work, we study an integrated inventory-transportation problem in a supply chain consisting of region-bound warehouses located in different regions. The supply chain deals with multiple items that compete for storage space and transportation capacity with multi-modal transportation considering regional capacity constraint for each mode of transportation. The objective is to determine an optimal storage and transportation plan to satisfy the demand of all regions without shortages for known procurement plan for all items. The problem is formulated as a mixed integer programming (MIP) model for minimizing the total costs over a finite planning horizon. An MIP-based fix-and-optimize (F&O) heuristic with several decomposition schemes is proposed to solve the problem efficiently. The performance of the decomposition schemes is investigated against the structure of the sub-problems obtained. To enhance the performance, F&O is crossbred with two metaheuristics – genetic algorithm (GA) and iterated local search (ILS) separately, which lead to hybrid heuristic approach. Extensive numerical experiments are carried out to analyze the performance of the proposed solution methodology by randomly generating several problem instances built using data collected from the Indian Public Distribution System. The proposed solution approach is found to be computationally efficient and effective, and outperforming state of the art MIP solver Cplex for practical size problem instances. Also, the hybridization of F&O heuristic with GA and ILS boosts its performance although with a justified increase in the computational time.
Mots-clés : inventory-transportation problem, fix-and-optimize, genetic algorithm, iterated local search, public distribution system
@article{RO_2020__54_3_749_0,
author = {Tanksale, Ajinkya and Jha, J.K.},
title = {A hybrid fix-and-optimize heuristic for integrated inventory-transportation problem in a multi-region multi-facility supply chain},
journal = {RAIRO - Operations Research - Recherche Op\'erationnelle},
pages = {749--782},
publisher = {EDP-Sciences},
volume = {54},
number = {3},
year = {2020},
doi = {10.1051/ro/2019025},
mrnumber = {4075323},
zbl = {1437.90022},
language = {en},
url = {http://www.numdam.org/articles/10.1051/ro/2019025/}
}
TY - JOUR AU - Tanksale, Ajinkya AU - Jha, J.K. TI - A hybrid fix-and-optimize heuristic for integrated inventory-transportation problem in a multi-region multi-facility supply chain JO - RAIRO - Operations Research - Recherche Opérationnelle PY - 2020 SP - 749 EP - 782 VL - 54 IS - 3 PB - EDP-Sciences UR - http://www.numdam.org/articles/10.1051/ro/2019025/ DO - 10.1051/ro/2019025 LA - en ID - RO_2020__54_3_749_0 ER -
%0 Journal Article %A Tanksale, Ajinkya %A Jha, J.K. %T A hybrid fix-and-optimize heuristic for integrated inventory-transportation problem in a multi-region multi-facility supply chain %J RAIRO - Operations Research - Recherche Opérationnelle %D 2020 %P 749-782 %V 54 %N 3 %I EDP-Sciences %U http://www.numdam.org/articles/10.1051/ro/2019025/ %R 10.1051/ro/2019025 %G en %F RO_2020__54_3_749_0
Tanksale, Ajinkya; Jha, J.K. A hybrid fix-and-optimize heuristic for integrated inventory-transportation problem in a multi-region multi-facility supply chain. RAIRO - Operations Research - Recherche Opérationnelle, Tome 54 (2020) no. 3, pp. 749-782. doi : 10.1051/ro/2019025. http://www.numdam.org/articles/10.1051/ro/2019025/
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