Scheduling is crucial since it maximizes productivity while lowering costs, lead times, cycle times, etc. An NP-hard combinatorial optimisation problem called the Flexible Job Shop Scheduling Problem (FJSSP) has several real-world applications, including industrial facilities and cloud computing. There has been a lot of interest in finding a solution because of how complicated and significant this problem is. The purpose of this study is to assess how well different flexible job shop scheduling strategies maximize production schedules. The study’s goal is to provide recommendations for selecting the best method for real-world industrial settings and other real-time applications. The current solution techniques for the FJSP are categorized as precise algorithms, heuristics, meta-heuristics and hybrid algorithms, In this work, a recent survey on hybrid techniques in the field of FJSS is thoroughly studied.