Heuristic algorithms for two-machine re-entrant flowshop scheduling problem with jobs of two classes

Abstract

This paper considers a two-machine re-entrant flowshop scheduling problem in which there are two classes of jobs with different urgencies, i.e., urgent jobs and normal (not urgent) jobs. The objective of this problem is minimizing total tardiness of one class of urgent jobs and maximum completion times of the other class of normal jobs. To solve this problem, a lower bound and several heuristic algorithms for the problem are proposed. To evaluate the performance of developed algorithms, computational experiments are performed on randomly generated problems, and results are reported with analysis. The suggested algorithms show better performances compared with the ones used in real manufacturing systems in terms of solution quality and computation time. Jeong and Shim, Journal of Advanced Mechanical Design, Systems, and Manufacturing, Vol.11, No.5 (2017) complete urgent jobs as early as possible since these jobs had very early due dates. In this problem, due dates of urgent jobs are set to the earliest possible completion times of the job on machine 2 (completion times of the job on machine 2 assuming that the job is processed through all machines without waiting). In this study, the objective of the problem is minimizing a weighted sum of total tardiness of urgent jobs and the maximum completion time of normal jobs.Re-entrant flowshop scheduling problems receive increasing attention in recent years. Graves et al. (1983) introduce a wafer fab in semi-conductor manufacturing system as a re-entrant flowshop and propose a simple scheduling algorithm for the re-entrant flowshop to minimize average throughput time while meeting a given production rate. Demirkol and Uzsoy (2000) suggest decomposition methods in a re-entrant flowshop for the objective of minimizing maximum lateness. Choi and Kim (2007) The problem in this study is one of the multi-objective flowshop problems since two types of measures are combined, i.e. weighted sum of total tardiness of urgent jobs and the maximum completion time of normal jobs. There have been various heuristic algorithms for multiple-objective flowshop problems including Rajendran and Ziegler (2004), Ravindran objective problems have two or more common objective functions for all jobs, this problem has a different objective function for jobs of a different class since jobs are classified into two classes according to their urgencies. Therefore, this problem is related to a multi-agent problem which is the special case of multi-objective problems. (Agnetis et al., 2004) Multi-agent problems consist of two or more agents (class or customers) and each agent has a different objective function for their jobs. That is, if we define each class of jobs as an agent, the problem in this paper can be regarded as a multiagent problem.Recently, multi-agent scheduling problems are also studied. Baker and Smith (2003) study weighted optimization problem for the multi-agent on single machine, the objectives including the maximum lateness, total weighted completion time and makespan. Agn...

Metaheuristics for a Flow Shop Scheduling Problem with Urgent Jobs and Limited Waiting Times

“…Simulated annealing (SA) is one of the most popular metaheuristic algorithms for combinatorial optimization problems including operations scheduling. In addition, SA showed good performance in a recent paper related to a two-machine flowshop with urgent jobs [1]. This study also adopts SA for the solution methodology.…”

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