A Hybrid GA for A Supply Chain Production Planning Problem

The problem of production and delivery lot-sizing and scheduling of set of items in a two-echelon supply chain over a finite planning horizon is addressed in this paper. A single supplier produces several items on a flexible flow line (FFL) production system and delivers them directly to ail assembly facility. Based on the well-known basic period (BP) policy, a new mixed zero-one nonlinear programming model has been developed to minimize average Setup, inventory-holding and delivery costs per unit time in the supply chain without any stock-out. The problem is very complex and it could not be solved to optimality especially in real-sized problems. So, an efficient hybrid genetic algorithm (HGA) using the most applied BP approach (i.e. power-of-two policy) has been proposed. The solution quality of the proposed algorithm called PT-HGA has been evaluated and compared with the common cycle approach in some problem instances. Numerical experiments demonstrate the merit of the PT-HGA and indicate that it is a very promising Solution method for the problem.