Fuzzy job-shop scheduling problems: A review

• A review and classification of fuzzy job shop scheduling problems (JSSPs).
• Variation of constraints and objectives investigated in Fuzzy JSSPs.
• Exact and heuristic methods applied on Fuzzy JSSPs.
• Meta-heuristic approaches applied on Fuzzy JSSPs at pre-processing, initialization and improvement steps.

Fuzzy job-shop scheduling problems (Fuzzy JSSPs) are a class of combinational optimization problems known as non-deterministic polynomial-hard problems. In recent decades, a number of researchers have expanded the theoretical models of Fuzzy JSSPs and introduced algorithms to solve them. This paper reviews the classification of Fuzzy JSSPs, constraints and objectives investigated in Fuzzy JSSPs, and the methodologies applied in solving Fuzzy JSSPs. The paper centers on reviewing meta-heuristic algorithms as state-of-the-art algorithms proposed for Fuzzy JSSPs. These algorithms are analyzed in three steps, namely, pre-processing, initialization procedures, and improvement algorithms. Finally, possible suggestions for future studies are obtained from this survey.