Abstract
In this study, we address an Inventory Routing Problem for hazardous and deteriorating pharmaceutical items in a healthcare network. Each hospital's demand is assumed to be deterministic but time varying over a finite planning horizon. Demand can be satisfied through a supply network, either from the main central pharmacy, or from other related hospitals' drugstores by allowing the transshipment option. The medicines deteriorate under a constant rate during the storage period. The proposed model is a bi-objective mixed integer mathematical programming. The first objective aims to minimize the total cost of logistics including ordering, transportation, delivery, pickup, shortage and inventory holding costs. The second objective function attempts to minimize the maximum accident loss during distribution among all periods. To consider the accident loss, for each route, two essential parameters are estimated based on historical data; the occurrence probability and severity index of accident. The model therefore attempts to utilize the best configuration of the routes and transshipment option to satisfy the demand while minimizing the costs and accident loss simultaneously. Several numerical examples are generated and solved by CPLEX and compared with the solutions of an efficient Hybrid Genetic Algorithm (HGA). The results show that the transshipment option not only can be used as a lever to increase the economic supply network performance through saving the routes, but also it can help the system to avoid risky routes.