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

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