scholarly journals Minimizing the Number of Tardy Jobs on a Single Machine with an Availability Constraint

2014 ◽  
Vol 2014 ◽  
pp. 1-13 ◽  
Author(s):  
Ehsan Molaee ◽  
Ghasem Moslehi

Most scheduling problems are based on the assumption that machines work continuously during the planning horizon. This assumption is not true in many production environments because the machine may not be available during one or more periods such as during breakdowns or maintenance operations. In this paper, the problem of the single machine scheduling with one unavailability period and nonresumable jobs with the aim of minimizing the number of tardy jobs is studied. A number of theorems are proved and a heuristic procedure is developed to solve the problem. A branch-and-bound approach is also presented which includes upper and lower bounds and efficient dominance rules. Computational results for 2680 problem instances show that the branch-and-bound approach is capable of solving 98.7% of the instances optimally, bearing witness to the efficiency of the proposed procedure. Our results also indicate that the proposed approaches are more efficient when compared to other methods.

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Jianbo Qian ◽  
George Steiner

We consider single machine scheduling problems with learning/deterioration effects and time-dependent processing times, with due date assignment consideration, and our objective is to minimize the weighted number of tardy jobs. By reducing all versions of the problem to an assignment problem, we solve them inO(n4) time. For some important special cases, the time complexity can be improved to beO(n2) using dynamic programming techniques.


2014 ◽  
Vol 624 ◽  
pp. 675-680
Author(s):  
Yu Fang Zhao

We studied single machine scheduling problems in which the jobs need to be delivered to customers after processing. It is assumed that the delivery times are proportional to the length of the already processed jobs, and a job's processing time depended on its position in a sequence. The objective functions include total earliness, the weighted number of tardy jobs and the cost of due date assignment. We analyzed these problems with two different due date assignment methods and conclude that the problems are polynomial time solvable.


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