A genetic algorithm for simultaneous optimisation of lot sizing and scheduling in a flow line assembly

This paper considers flexible flow line assembly, which assembles various models of a single product. Lot sizing in procurement and production scheduling are considered as the two critical factors to control the cost of production in those units. The simultaneous optimisation of procurement lot sizing, and the assembly scheduling offer many benefits. Literature review has shown that only a little consideration is given to setup time dependent production system with order backlog. An integrated cost model including setup time dependency and order backlog is developed to handle both procurement lot sizing and production scheduling simultaneously. This paper proposes a genetic algorithm (GA) based heuristic to evolve optimal or near optimal solution for flow line assembly problem. LINGO Solver, an integer programming tool, is used to evaluate the performance of the proposed algorithm under independent setup time considerations. The comparison reveals that the proposed GA is able to give optimal or closer to optimal solutions. But the significance of GA is its capability of optimising the production sequence and the production quantity simultaneously under the setup dependent environment.