Inventory control in healthcare supply chain management using apriori and gravitational search algorithms

Valan, J. Arul; Baburaj, E.

doi:10.1504/ijlsm.2020.106270

Cited by 2 publications

(1 citation statement)

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“…Tat et al (2020) also suggested a mathematical model for PSCM by incorporating the reselling medicines in the alternative market but do not consider the delivery time of the pharmaceutical products. Valan and Baburaj (2020) also suggested a prior and gravitational algorithm for inventory control in the PSC planning problem. Wang and Jie (2019) attempted to reduce the risk and uncertainty in the PSCM network.…”

Section: Literature Reviewmentioning

confidence: 99%

A fuzzy quantitative model for assessing the performance of pharmaceutical supply chain under uncertainty

Ahmad

John

2021

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PurposeThis study aims to investigate a reliability-level demand-oriented pharmaceutical supply chain design with maximal anticipated demand coverage. Different hospitals with the particular reliability value associated with the various pharmaceutical items (PIs) are considered. An inter-connected multi-period supply chain comprising manufacturers, distribution centers, hospitals and patients is assumed for the smooth flow of health-care items, enhancing supply chain reliability. A reliability index for PIs is depicted to highlight product preference and facilitate hospitals’ service levels for patients.Design/methodology/approachA mixed-integer multi-objective programming problem that maximizes maximal demand coverage minimizes the total economic costs and pharmaceutical delivery time is depicted under intuitionistic fuzzy uncertainty. Further, a novel interactive neutrosophic programming approach is developed to solve the proposed pharmaceutical supply chain management (PSCM) model. Each objective’s marginal evaluation is elicited by various sorts of membership functions such as linear, exponential and hyperbolic types of membership functions and depicted the truth, indeterminacy and falsity membership degrees under a neutrosophic environment.FindingsThe proposed PSCM model is implemented on a real case study and solved using an interactive neutrosophic programming approach that reveals the proposed methods’ validity and applicability. An ample opportunity to generate the compromise solution is suggested by tuning various parameters. The outcomes are evaluated with practical managerial implications based on the significant findings. Finally, conclusions and future research scope are addressed based on the proposed work.Research limitations/implicationsThe propounded study has some limitations that can be addressed in future research. The discussed PSCM model can be merged with and extended by considering environmental factors such as the health-care waste management system, which is not included in this study. Uncertainty among parameters due to randomness can be incorporated and can be tackled with historical data. Besides, proposed interactive neutrosophic programming approach (INPA), various metaheuristic approaches may be applied to solve the proposed PSCM model as a future research scope.Practical implicationsThe strategy advised is to provide an opportunity to create supply chains and manufacturing within India by helping existing manufacturers to expand, identifying new manufacturers, hand-holding and facilitating, teams of officers, engineers and scientists deployed and import only if necessary to meet timelines. Thus, any pharmaceutical company or organization can adopt the production and distribution management initiatives amongst hospitals to strengthen and enable the pharmaceutical company while fighting fatal diseases during emergencies. Finally, managers or policy-makers can take advantage of the current study and extract fruitful pieces of information and knowledge regarding the optimal production and distribution strategies while making decisions.Originality/valueThis research work manifests the demand-oriented extension of the integrated PSCM design with maximum expected coverage, where different hospitals with pre-determined reliability values for various PIs are taken into consideration. The practical managerial implications are explored that immensely support the managers or practitioners to adopt the production and distribution policies for the PIs to ensure the sustainability in supply chain design.

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Section: Literature Reviewmentioning

confidence: 99%

A fuzzy quantitative model for assessing the performance of pharmaceutical supply chain under uncertainty

Ahmad

John

2021

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Current studies and applications of Krill Herd and Gravitational Search Algorithms in healthcare

Hamad

Rashid

2023

Artif Intell Rev

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Inventory control in healthcare supply chain management using apriori and gravitational search algorithms

Cited by 2 publications

References 0 publications

A fuzzy quantitative model for assessing the performance of pharmaceutical supply chain under uncertainty

A fuzzy quantitative model for assessing the performance of pharmaceutical supply chain under uncertainty

Current studies and applications of Krill Herd and Gravitational Search Algorithms in healthcare

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