An enhanced migrating birds optimization algorithm for no-wait flow shop scheduling problem

No-wait flow shop scheduling problem has important applications in industrial systems. Migrating birds optimization (MBO) algorithm is a new meta-heuristic inspired by the V flight formation of the migrating birds which is proven to be an effective energy saving formation. This paper proposes an enhanced migrating birds optimization (EMBO) algorithm for no-wait flow shop scheduling with total flow time criterion. Because MBO is a neighborhood-based search heuristic, the population is divided into multiple migrating birds in proposed EMBO in an attempt to avoid local optima. Three heuristics are used for initializing the population. An effective neighborhood structure is used for each loop of EMBO. Extensive computational experiments are carried out based on a set of well-known flow shop benchmark instances that are considered as no-wait flow shop instances. Computational results and comparisons show that the proposed EMBO algorithm performs significantly better than the existing ones for no-wait flow shop scheduling problem with total flow time criterion.