Logistic planning for pharmaceutical supply chain using multi-objective optimization model
International Journal of Pharmaceutical and Healthcare Marketing
ISSN: 1750-6123
Article publication date: 3 November 2021
Issue publication date: 11 February 2022
Abstract
Purpose
Appropriate logistic planning for the pharmaceutical supply chain can significantly improve many financial and performance aspects. To this aim, a multi-objective optimization model is proposed in this paper that considers different types of pharmaceuticals, different vehicles with determining capacities and multi-period logistic planning. This model can be updated based on new information about resources and newly identified requests.
Design/methodology/approach
The main objective function of the proposed model in this paper is minimizing the unsatisfied prioritized requests for pharmaceuticals in the network. Besides, the total transportation activities of different types of vehicles and related costs are considered as other objectives. Therefore, these objectives are optimized hierarchically in the proposed model using the Lexicographic method. This method finds the best value for the first objective function. Then, it tries to optimize the second objective function while maintaining the optimality of the first objective function. The third objective function is optimized based on the optimality of other objective functions, as well. A non-dominated sorting genetic algorithm II-multi-objective particle swarm optimization heuristic method is designed for this aim.
Findings
The performances of the proposed model were analyzed in different cases and its results for different problems were shown within the framework of a case study. Besides, the sensitivity analysis of results shows the logical behavior of the proposed model against various factors.
Practical implications
The proposed methodology can be applied to find the best logistic plan in real situations.
Originality/value
In this paper, the authors have tried to use a multi-objective optimization model to guide and correct the pharmaceutical supply chain to deal with the related requests. This is important because it can help managers to improve their plans.
Keywords
Acknowledgements
The authors wish to thank Dr S. Ershadi and Dr E. Mohaghegh, for providing the expert’s knowledge used in this research. The authors also thank Eng. Y. Afshari and Dr M. Eghdami (experts of Isfahan welfare organization), Dr A. Binaee (experts of Isfahan ministry of health), and Dr S. Ahmadi (expert of Isfahan municipality organization) for their cooperation for providing various information.
Funding Information: All authors declare that for this paper, there is no any fund to support it financially. No funding was received.
Disclosure of potential conflicts of interest: There is not any conflict of interest to declare by the authors.
Research involving human participants and/or animals: This article does not contain any studies with human or animals participants performed by any of the authors.
Informed Consent: Informed consent was obtained from all individual participants included in the study. This statement is to certify that all authors have seen and approved the manuscript being submitted in International Journal of Pharmaceutical and Healthcare Marketing. We warrant that the article is the authors' original work. We warrant that the article has not received prior publication and is not under consideration for publication elsewhere. On behalf of all co-authors, the corresponding author shall bear full responsibility for the submission. This research has not been submitted for publication nor has it been published in whole or in part elsewhere. All authors agree that author list is correct in its content and order.
Citation
Ershadi, M.M. and Ershadi, M.S. (2022), "Logistic planning for pharmaceutical supply chain using multi-objective optimization model", International Journal of Pharmaceutical and Healthcare Marketing, Vol. 16 No. 1, pp. 75-100. https://doi.org/10.1108/IJPHM-01-2021-0004
Publisher
:Emerald Publishing Limited
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