Operational decisions in automated guided vehicles-served flowshop loops: Scheduling

This paper considers operational issues that arise in repetitive manufacturing systems served by automated guided vehicles (AGVs) in loops with unidirectional material flow. The objective considered is the minimization of the steady state cycle time required to produce a minimal job set (or equivalently, throughput rate maximization). Our models allow for delays caused by AGV conflicts. We define and analyze three nondominated and widely used AGV dispatching policies. For each policy, we describe algorithms and intractability results for combined job scheduling and material handling problems. We describe a genetic algorithm that estimates the cycle time within 5% on average for instances with up to 10 machines and four AGVs. Some related fleet sizing and loop decomposition issues are discussed in the companion paper (next abstract).