scholarly journals A note on worst-case performance of heuristics for maintenance scheduling problems

2007 ◽  
Vol 155 (3) ◽  
pp. 416-422 ◽  
Author(s):  
Xiangtong Qi
Keyword(s):  
Maintenance Scheduling ◽  
Scheduling Problems ◽  
Worst Case

scholarly journals Two Parallel-Machine Scheduling Problems with Function Constraint

2020 ◽  
Vol 2020 ◽  
pp. 1-6 ◽  
Author(s):  
Chia-Lun Hsu ◽  
Jan-Ray Liao
Keyword(s):  
Completion Time ◽  
Machine Scheduling ◽  
Parallel Machine Scheduling ◽  
Parallel Machine ◽  
Total Completion Time ◽  
Scheduling Problems ◽  
Worst Case ◽  
Time Problem ◽  
Constraint Problem ◽  
Machine Scheduling Problems

The objective of this paper is to minimize both the makespan and the total completion time. Since parallel-machine scheduling which contains the function constraint problem has been a new issue, this paper explored two parallel-machine scheduling problems with function constraint, which refers to the situation that the two machines have a same function but one of the machines has another. We pointed out that the function constraint occurs not only in the manufacturing system but also in the service system. For the makespan problem, we demonstrated that it is NP-hard in the ordinary sense. In addition, we presented a polynomial time heuristic for this problem and have proved its worst-case ratio is not greater than 5/4. Furthermore, we simulated the performance of the algorithm through computational testing. The overall mean percent error of the heuristic is 0.0565%. The results revealed that the proposed algorithm is quite efficient. For the total completion time problem, we have proved that it can be solved in On4 time.

Scheduling two classes of exponential jobs on parallel processors: structural results and worst-case analysis

1991 ◽  
Vol 23 (4) ◽  
pp. 925-944 ◽  
Author(s):  
Cheng-Shang Chang ◽  
Randolph Nelson ◽  
Michael Pinedo
Keyword(s):  
Case Analysis ◽  
Parallel Processors ◽  
Worst Case Analysis ◽  
Weighted Sum ◽  
Scheduling Problems ◽  
Worst Case ◽  
Total Cost ◽  
Class 1 ◽  
Completion Times ◽  
Sum Of Completion Times

In this paper, we consider scheduling problems with m machines in parallel and two classes of job. We assume that all jobs are present at time 0 and there are no further arrivals. The service times of class 1 (2) jobs are independent and exponentially distributed with mean . Each class 1 (2) job incurs a cost c1 (c2) per unit of time until it leaves the system. The objective is to minimize the expected total cost, that is the expected weighted sum of completion times. We show that the optimal policy among all preemptive policies is of threshold type. Based on these structural results, we also show that the ratio of the expected weighted sum of completion times under the cµ-rule to that under the optimal rule is less than 1·71.

Scheduling two classes of exponential jobs on parallel processors: structural results and worst-case analysis

1991 ◽  
Vol 23 (04) ◽  
pp. 925-944 ◽  
Author(s):  
Cheng-Shang Chang ◽  
Randolph Nelson ◽  
Michael Pinedo
Keyword(s):  
Case Analysis ◽  
Parallel Processors ◽  
Worst Case Analysis ◽  
Weighted Sum ◽  
Scheduling Problems ◽  
Worst Case ◽  
Total Cost ◽  
Class 1 ◽  
Completion Times ◽  
Sum Of Completion Times

In this paper, we consider scheduling problems with m machines in parallel and two classes of job. We assume that all jobs are present at time 0 and there are no further arrivals. The service times of class 1 (2) jobs are independent and exponentially distributed with mean . Each class 1 (2) job incurs a cost c 1 (c 2) per unit of time until it leaves the system. The objective is to minimize the expected total cost, that is the expected weighted sum of completion times. We show that the optimal policy among all preemptive policies is of threshold type. Based on these structural results, we also show that the ratio of the expected weighted sum of completion times under the cµ-rule to that under the optimal rule is less than 1·71.

A zero-one integer programming for preventive maintenance scheduling for electricity and distiller plants with production

2019 ◽  
Vol 26 (4) ◽  
pp. 555-574
Author(s):  
Khaled Alhamad ◽  
Mohammad Alhajri
Keyword(s):  
Integer Programming ◽  
Preventive Maintenance ◽  
Programming Model ◽  
Practical Method ◽  
Maintenance Scheduling ◽  
Scheduling Problems ◽  
Cogeneration Plant ◽  
Content Type ◽  
Proposed Model ◽  
Effective Decision Making

Purpose The purpose of this paper is to describe a method that has been set up to schedule preventive maintenance (PM) tasks for power and water plants with all constraints such as production and maintenance. Design/methodology/approach The proposed methodology relies on the zero-one integer programming model that finds the maximum number of power and water units available in separate generating units. To verify this, the model was implemented and tested as a case study in Kuwait for the Cogeneration Station. Findings An effective solution can be achieved for scheduling the PM tasks and production at the power and water cogeneration plant. Practical implications The proposed model offers a practical method to schedule PM of power and water units, which are expensive equipment. Originality/value This proposed model is an effective decision-making tool that provides an ideal solution for preventive maintenance scheduling problems for power and water units in a cogeneration plant, effectively and complies with all constraints.

Sign in / Sign up

Export Citation Format

Share Document