Five-Echelon Multiobjective Health Services Supply Chain Modeling under Disruption

Abstract

Medicine unreliability problem is taken into consideration as one of the most important issues in health supply chain management. This research is associated with the development of a multiobjective optimization problem for the selection of suppliers and distributors. To achieve the purposes, the optimal quota allocation is determined with respect to disruption of suppliers in a five-echelon supply chain network and consideration of the distributor centers as a hub location-allocation mode. The objective of the optimization model is involved in simultaneous minimization of transactions costs dealing with suppliers, expected purchasing costs from suppliers, expected percentages of delayed and returned products in each distributor, as well as transportation cost in each echelon and fixed cost for distributor centers, and finally maximization of the expected scores for suppliers and high priority of product customers. The optimization problem is formulated as a mixed-integer nonlinear programming model. The proposed optimization model is utilized to investigate a numerical case study for asthma-specific medicines. The analyzing procedure is conducted based on the collected real data from Cobel Darou pharmaceutical company in 2019. Furthermore, a fuzzy multichoice goal programming model is considered to solve the proposed optimization model by R optimization solver. The numerical results confirmed the authenticity of the model.

Investigating the Optimality of Existing Hubs in Terms of Coverage Capacity and Locating New Hubs for the Green Supply Chain of Medical and Pharmaceutical Equipment

“…Hence, in terms of credit value, the value of the hubs is more likely to grow [2]. Selection is the appropriate place to manage the management of pharmaceutical equipment companies [3]. In recent years, various decisions and policies have been taken in order to reduce the costs of medical equipment manufacturing companies, which is one of the most important issues in reducing costs, choosing the location and distribution centers.…”