Physical distribution (transportation) of goods and services from multiple supply centers to multiple demand centers is an important application of linear programming (LP). A transportation problem (TP) can also be solved using the simplex method when expressed as an LP model. However, because a TP has a large number of variables and constraints, solving it using simplex methods takes a long time. Many scientists have devised and continue to devise novel solutions to the classic TP. The prohibited route transportation problem, on the other hand, is a subset of TPs for which most scientists have yet to develop a specific TP. Certain routes may be impassable in some cases due to transportation issues. To name a few: construction projects, poor road conditions, strikes, unexpected disasters, and local traffic laws. Such limits (or prohibitions) in the TP can be managed by assigning a very high cost to the prohibited routes, ensuring that they do not appear in the optimal solution. This paper presents a heuristic algorithm and an improved ant colony optimization algorithm for achieving an initial feasible solution (IFS) to a prohibitive transportation problem (PTP). Using the PTP in the proposed method, on the other hand, produces the best IFS for a prohibited transportation problem and outperforms existing methods with less computation time and complexity. As a result, the proposed methods are an appealing alternative to traditional problem-solving approaches. In some numerical examples, the feasible solution of the proposed method is the same as the optimal solution.
| Published in | International Journal of Applied Mathematics and Theoretical Physics (Volume 8, Issue 2) |
| DOI | 10.11648/j.ijamtp.20220802.12 |
| Page(s) | 43-51 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
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Copyright © The Author(s), 2022. Published by Science Publishing Group |
Ant Colony Optimization Algorithm, Initial Feasible Solution, Optimal Solution, Prohibited Transportation Problems, Transportation Problem
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APA Style
Ekanayake Mudiyanselage Uthpala Senarath Bandara Ekanayake. (2022). An Improved Ant Colony Algorithm to Solve Prohibited Transportation Problems. International Journal of Applied Mathematics and Theoretical Physics, 8(2), 43-51. https://doi.org/10.11648/j.ijamtp.20220802.12
ACS Style
Ekanayake Mudiyanselage Uthpala Senarath Bandara Ekanayake. An Improved Ant Colony Algorithm to Solve Prohibited Transportation Problems. Int. J. Appl. Math. Theor. Phys. 2022, 8(2), 43-51. doi: 10.11648/j.ijamtp.20220802.12
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Download@article{10.11648/j.ijamtp.20220802.12,
author = {Ekanayake Mudiyanselage Uthpala Senarath Bandara Ekanayake},
title = {An Improved Ant Colony Algorithm to Solve Prohibited Transportation Problems},
journal = {International Journal of Applied Mathematics and Theoretical Physics},
volume = {8},
number = {2},
pages = {43-51},
doi = {10.11648/j.ijamtp.20220802.12},
url = {https://doi.org/10.11648/j.ijamtp.20220802.12},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijamtp.20220802.12},
abstract = {Physical distribution (transportation) of goods and services from multiple supply centers to multiple demand centers is an important application of linear programming (LP). A transportation problem (TP) can also be solved using the simplex method when expressed as an LP model. However, because a TP has a large number of variables and constraints, solving it using simplex methods takes a long time. Many scientists have devised and continue to devise novel solutions to the classic TP. The prohibited route transportation problem, on the other hand, is a subset of TPs for which most scientists have yet to develop a specific TP. Certain routes may be impassable in some cases due to transportation issues. To name a few: construction projects, poor road conditions, strikes, unexpected disasters, and local traffic laws. Such limits (or prohibitions) in the TP can be managed by assigning a very high cost to the prohibited routes, ensuring that they do not appear in the optimal solution. This paper presents a heuristic algorithm and an improved ant colony optimization algorithm for achieving an initial feasible solution (IFS) to a prohibitive transportation problem (PTP). Using the PTP in the proposed method, on the other hand, produces the best IFS for a prohibited transportation problem and outperforms existing methods with less computation time and complexity. As a result, the proposed methods are an appealing alternative to traditional problem-solving approaches. In some numerical examples, the feasible solution of the proposed method is the same as the optimal solution.},
year = {2022}
}
TY - JOUR T1 - An Improved Ant Colony Algorithm to Solve Prohibited Transportation Problems AU - Ekanayake Mudiyanselage Uthpala Senarath Bandara Ekanayake Y1 - 2022/09/27 PY - 2022 N1 - https://doi.org/10.11648/j.ijamtp.20220802.12 DO - 10.11648/j.ijamtp.20220802.12 T2 - International Journal of Applied Mathematics and Theoretical Physics JF - International Journal of Applied Mathematics and Theoretical Physics JO - International Journal of Applied Mathematics and Theoretical Physics SP - 43 EP - 51 PB - Science Publishing Group SN - 2575-5927 UR - https://doi.org/10.11648/j.ijamtp.20220802.12 AB - Physical distribution (transportation) of goods and services from multiple supply centers to multiple demand centers is an important application of linear programming (LP). A transportation problem (TP) can also be solved using the simplex method when expressed as an LP model. However, because a TP has a large number of variables and constraints, solving it using simplex methods takes a long time. Many scientists have devised and continue to devise novel solutions to the classic TP. The prohibited route transportation problem, on the other hand, is a subset of TPs for which most scientists have yet to develop a specific TP. Certain routes may be impassable in some cases due to transportation issues. To name a few: construction projects, poor road conditions, strikes, unexpected disasters, and local traffic laws. Such limits (or prohibitions) in the TP can be managed by assigning a very high cost to the prohibited routes, ensuring that they do not appear in the optimal solution. This paper presents a heuristic algorithm and an improved ant colony optimization algorithm for achieving an initial feasible solution (IFS) to a prohibitive transportation problem (PTP). Using the PTP in the proposed method, on the other hand, produces the best IFS for a prohibited transportation problem and outperforms existing methods with less computation time and complexity. As a result, the proposed methods are an appealing alternative to traditional problem-solving approaches. In some numerical examples, the feasible solution of the proposed method is the same as the optimal solution. VL - 8 IS - 2 ER -
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