A Hybrid Tabu Search Algorithm For Constraint Flowshop Scheduling Problems

Job sequencing and job plan problem are general problem in service,carrying trade and all kinds of enterprise producing. This is a job sequencing and job plan problem that how to repair these machines that are breakdown under existing serving condition for the entire lost reaching minimum value. The job scheduling is a kind of job sequencing and important to advance work efficiency and economic performance. The job scheduling problems may be characterized by different flow patterns of the jobs. The flow pattern may be the same for all the jobs(flow shop),or each job may have its own individual flow pattern(job shop).A no-wait flow shop problem occurs when the operations of a job have to be processed continuously from start to end without interruptions either on or between machines. Because this constraint is more relevant and meaningful for today's dynamic producing environment and the quality of products, such as the metal and food industries. Whereas the practice and application of no-wait flow shop, many researchers have pay more attention to this area and proposed approaches for solving these problems.Shop scheduling problem is typically NP-hard, which means that it is impossible to find the global optimum in polynomial complexity. In recent years, meta-heuristic and heuristic are two kinds of algorithms for job scheduling. However, they are different in CPU-time and performance. Meta-heuristic can always obtain better solutions than heuristic, but they need more CPU-time. As well, robustness of heuristic is good but optimum can seldom be obtained. For better solving shop scheduling, this is popular that the quality of solutions is pursued by most researchers at present by integrating some heuristic with a meta-heuristic.Applying single heuristic algorithm can not acquire optimum solution and the...