The flow shop scheduling problem (FSSP) is one of the most scientifically studied scheduling problems. In the FSSP, a set of n independent jobs have to be processed on a set of m machines. Every job requires a given fixed, nonnegative processing time on every machine. Traditional flow shop scheduling problems were primarily focused on the objectives related to completion time of jobs, on the other hand, in current manufacturing tradition, on time delivery is a noteworthy criterion to stay in the rapidly growing markets. As customers expectations are to get ordered goods to be delivered on time. So industries focus has gone beyond the single objective scheduling system. The primary objective of flow shop scheduling is to obtain the best sequence, which minimizes the various objectives like makespan, flow time, idle time, work inprocess and tardiness, etc. To optimize the objectives there are various method such as Tabu search, genetic algorithms and simulated annealing etc. have been developed. Among these methods, Simulated Annealing (SA) is believed to be the valuable search algorithm to accomplish the objectives. The present work is the review of simulated annealing for flow shop scheduling problems and classified based on various criteria of SA such as its parameter selection, computer resource usage, hybridization and enhancement from the past work.
Scheduling, Flow shop, Simulated annealing, Survey, Review
