Assembly Sequence Planning (ASP) is one of the important optimization problems in manufacturing. Optimum assembly sequence is difficult due to various reasons: As ASP is a NP hard combinatorial problem, achieving the optimum assembly sequence is a difficulty process. Moreover, ASP problem is multi-model optimization problem where a product can assemble in many possible ways. As the part count in the assembly increases, the time for assembly is more and obtaining the optimum assembly sequences is difficult. Many mathematical algorithms are proposed to obtain optimum solutions, which performs poorly. Meanwhile researchers are motivated towards developing the Artificial Intelligence (AI) techniques to solve ASP problems due to their less search space for implementing even the complex assemblies. The challenging task in ASP problem is automatic extraction assembly constraints to obtain the optimum assembly sequence. Keeping this thing in mind, in this paper, a Modified BAT Algorithm (MBA) has been implemented to solve ASP problem. In this paper first time BAT algorithm is applied to solve discrete optimization problem. © Published under licence by IOP Publishing Ltd.