Designing a new medicine supply chain network considering production technology policy using two novel heuristic algorithms

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27510%2F21%3A10247577" target="_blank" >RIV/61989100:27510/21:10247577 - isvavai.cz</a>

Result on the web

<a href="https://www.rairo-ro.org/articles/ro/pdf/2021/03/ro200076.pdf" target="_blank" >https://www.rairo-ro.org/articles/ro/pdf/2021/03/ro200076.pdf</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1051/ro/2021031" target="_blank" >10.1051/ro/2021031</a>

Result language

angličtina

Original language name

Designing a new medicine supply chain network considering production technology policy using two novel heuristic algorithms

Original language description

The role of medicines in health systems is increasing day by day. The medicine supply chain is a part of the health system that if not properly addressed, the concept of health in that community is unlikely to experience significant growth. To fill gaps and available challenging in the medicine supply chain network (MSCN), in the present paper, efforts have been made to propose a location-production-distribution-transportation-inventory holding problem for a multi-echelon multi-product multi-period bi-objective MSCN network under production technology policy. To design the network, a mixed-integer linear programming (MILP) model capable of minimizing the total costs of the network and the total time the transportation is developed. As the developed model was NP-hard, several meta-heuristic algorithms are used and two heuristic algorithms, namely, Improved Ant Colony Optimization (IACO) and Improved Harmony Search (IHS) algorithms are developed to solve the MSCN model in different problems. Then, some experiments were designed and solved by an optimization solver called GAMS (CPLEX) and the presented algorithms to validate the model and effectiveness of the presented algorithms. Comparison of the provided results by the presented algorithms and the exact solution is indicative of the high-quality efficiency and performance of the proposed algorithm to find a near-optimal solution within reasonable computational time. Hence, the results are compared with commercial solvers (GAMS) with the suggested algorithms in the small-sized problems and then the results of the proposed meta-heuristic algorithms with the heuristic methods are compared with each other in the large-sized problems. To tune and control the parameters of the proposed algorithms, the Taguchi method is utilized. To validate the proposed algorithms and the MSCN model, assessment metrics are used and a few sensitivity analyses are stated, respectively. The results demonstrate the high quality of the proposed IACO algorithm.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

10103 - Statistics and probability

Project

—

Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2021

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

RAIRO - Operations Research

ISSN

0399-0559

e-ISSN

—

Volume of the periodical

55

Issue of the periodical within the volume

2

Country of publishing house

FR - FRANCE

Number of pages

28

Pages from-to

1015-1042

UT code for WoS article

000647643300004

EID of the result in the Scopus database

2-s2.0-85105754548