Scheduling step-deteriorating jobs to minimize the total weighted tardiness on a single machine
Peng Guo, Wenming Cheng, Yi Wang
Abstract
Open-access reader
Peng Guo, Wenming Cheng, Yi Wang
Abstract
Open-access reader
This paper addresses the scheduling problem of minimizing the total weighted tardiness on a single machine with step-deteriorating jobs. With the assumption of deterioration, the job processing times are modeled by step functions of job starting times and pre-specified job deteriorating dates. The introduction of step-deteriorating jobs makes a single machine total weighted tardiness problem more intractable. The computational complexity of this problem under consideration was not determined. In this study, it is firstly proved to be strongly NP-hard. Then a mixed integer programming model is derived for solving the problem instances optimally. In order to tackle large-sized problems, seven dispatching heuristic procedures are developed for near-optimal solutions. Meanwhile, the solutions delivered by the proposed heuristic are further improved by a pair-wise swap movement. Computational results are presented to reveal the performance of all proposed approaches.
A significance statement is not available in the OpenAlex record.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
This paper addresses the scheduling problem of minimizing the total weighted tardiness on a single machine with step-deteriorating jobs. With the assumption of deterioration, the job processing times are modeled by step functions of job starting times and pre-specified job deteriorating dates. The introduction of step-deteriorating jobs makes a single machine total weighted tardiness problem more intractable. The computational complexity of this problem under consideration was not determined. In this study, it is firstly proved to be strongly NP-hard. Then a mixed integer programming model is derived for solving the problem instances optimally. In order to tackle large-sized problems, seven dispatching heuristic procedures are developed for near-optimal solutions. Meanwhile, the solutions delivered by the proposed heuristic are further improved by a pair-wise swap movement. Computational results are presented to reveal the performance of all proposed approaches.
Key concepts: Tardiness, Single-machine scheduling, Mathematical optimization, Computer science, Scheduling (production processes), Swap (finance), Due date, Job shop scheduling