A discrete fruit fly optimization algorithm for flow shop scheduling problem with intermingling equal sublots

A discrete fruit fly optimization algorithm (DFOA) is proposed in this paper to solve the flow shop scheduling problem with intermingling equal sublots (FSP-IES). Two main search procedures are designed in the DFOA to well balance the exploitation and exploration abilities, i.e., the neighborhood-based search and the global cooperation-based search. To handle the intermingling characteristic of the problem, two types of neighborhood structures and a self-adaptive selecting mechanism are presented for generating new solutions. To analyze the effect of parameter setting on the DFOA, investigation based on the design of experiment is carried out. Finally, computational results and comparisons demonstrate the effectiveness of the proposed DFOA.