Single facility scheduling with nonlinear processing times
Computers and Industrial Engineering
Scheduling deteriorating jobs on a single processor
Operations Research
Scheduling jobs under simple linear deterioration
Computers and Operations Research
The complexity of scheduling starting time dependent tasks with release times
Information Processing Letters
Minimizing the total weighted completion time of deteriorating jobs
Information Processing Letters
Minimizing the weighted number of tardy jobs on a two-machine flow shop
Computers and Operations Research
Information Processing Letters
An Exact Method to Minimize the Number of Tardy Jobs in Single Machine Scheduling
Journal of Scheduling
Scheduling linear deteriorating jobs with an availability constraint on a single machine
Theoretical Computer Science
Scheduling deteriorating jobs on a single machine with release times
Computers and Industrial Engineering
Scheduling Algorithms
Minimizing the number of tardy jobs under piecewise-linear deterioration
Computers and Industrial Engineering
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In this paper a problem of scheduling a single machine under linear deterioration which aims at minimizing the number of tardy jobs is considered. According to our assumption, processing time of each job is dependent on its starting time based on a linear function where all the jobs have the same deterioration rate. It is proved that the problem is NP-hard; hence a branch and bound procedure and a heuristic algorithm with O(n 2) is proposed where the heuristic one is utilized for obtaining the upper bound of the B&B procedure. Computational results for 1,800 sample problems demonstrate that the B&B method can solve problems with 28 jobs quickly and in some other groups larger problems are also solved. Generally, B&B method can optimally solve 85% of the samples which shows high performance of the proposed method. Also it is shown that the average value of the ratio of optimal solution to the heuristic algorithm result with the objective 驴(1 驴 Ui) is at most 1.11 which is more efficient in comparison to other proposed algorithms in related studies in the literature.