TY - GEN
T1 - An Optimization Method for a Multi-day Distribution Problem with Shortage Supplies
AU - Amphaiphan, Netiphan
AU - Laesanklang, Wasakorn
N1 - Publisher Copyright:
© 2022 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved.
PY - 2020
Y1 - 2020
N2 - We investigated a multi-day distribution problem while supplies are limited. This scenario can be found in post-natural disasters or economic crisis such as floods, earthquakes, palm oil shortage crisis, etc. The objective function of this problem is to minimize total traveling distance, unsatisfied cost, and variance of supply delivery proportion. In order to solve this multi-day problem optimally, it requires large computing memory and takes a long computational time. Therefore, we divided these large problems into multiple daily sub-problems and solved the sub-problems with the exact method. The sub-problems were solved sequentially for which the prior daily sub-problem is to be tackle first and the following daily sub-problems are defined based on the prior daily sub-problem solution. Changes were applied to update demands and to adjust delivery priority. There are three delivery priority setups proposing in this paper. Also, we present an experiment using the three proposed methods to solve modified Solomon’s vehicle routing problem datasets which extended a single period vehicle routing problem with time windows to be seven-day routing problems.
AB - We investigated a multi-day distribution problem while supplies are limited. This scenario can be found in post-natural disasters or economic crisis such as floods, earthquakes, palm oil shortage crisis, etc. The objective function of this problem is to minimize total traveling distance, unsatisfied cost, and variance of supply delivery proportion. In order to solve this multi-day problem optimally, it requires large computing memory and takes a long computational time. Therefore, we divided these large problems into multiple daily sub-problems and solved the sub-problems with the exact method. The sub-problems were solved sequentially for which the prior daily sub-problem is to be tackle first and the following daily sub-problems are defined based on the prior daily sub-problem solution. Changes were applied to update demands and to adjust delivery priority. There are three delivery priority setups proposing in this paper. Also, we present an experiment using the three proposed methods to solve modified Solomon’s vehicle routing problem datasets which extended a single period vehicle routing problem with time windows to be seven-day routing problems.
KW - Distribution
KW - Mixed Integer Programming Model
KW - Multi-period Vehicle Routing Problem
KW - Shortage Supplies
UR - http://www.scopus.com/inward/record.url?scp=85172791945&partnerID=8YFLogxK
U2 - 10.5220/0009154703560363
DO - 10.5220/0009154703560363
M3 - Conference contribution
AN - SCOPUS:85172791945
SN - 9789897583964
T3 - International Conference on Operations Research and Enterprise Systems
SP - 356
EP - 363
BT - ICORES 2020 - Proceedings of the 9th International Conference on Operations Research and Enterprise Systems
A2 - Parlier, Greg H.
A2 - Liberatore, Federico
A2 - Demange, Marc
PB - Science and Technology Publications, Lda
T2 - 9th International Conference on Operations Research and Enterprise Systems, ICORES 2020
Y2 - 22 February 2020 through 24 February 2020
ER -