A note on a single machine scheduling problem with generalized total tardiness objective function

2012 ◽  
Vol 112 (3) ◽  
pp. 72-76 ◽  
Author(s):  
Evgeny R. Gafarov ◽  
Alexander A. Lazarev ◽  
Frank Werner
Keyword(s):  
Objective Function ◽  
Single Machine ◽  
Machine Scheduling ◽  
Single Machine Scheduling ◽  
Total Tardiness ◽  
Scheduling Problem

SOME IMPROVED ALGORITHMS ON THE SINGLE MACHINE HIERARCHICAL SCHEDULING WITH TOTAL TARDINESS AS THE PRIMARY CRITERION

2010 ◽  
Vol 27 (05) ◽  
pp. 577-585 ◽  
Author(s):  
CHENG HE ◽  
YIXUN LIN ◽  
JINJIANG YUAN
Keyword(s):  
Single Machine ◽  
Machine Scheduling ◽  
Single Machine Scheduling ◽  
Total Tardiness ◽  
Scheduling Problem ◽  
Np Hard ◽  
Assignment Problems ◽  
Running Time ◽  
Minimization Problems ◽  
Hierarchical Minimization

It is well-known that a single machine scheduling problem of minimizing the total tardiness is NP-hard. Recently, Liu, Ng and Cheng solved some special hierarchical minimization problems with total tardiness as the primary criterion by the Algorithm TAP (Two Assignment Problems) in O(n3) time. And in this paper we present some algorithms for these problems with running time O(n log n).

An Optimal Algorithm for Scheduling with Variable Job Processing Times and Rejection

2015 ◽  
Vol 775 ◽  
pp. 449-452
Author(s):  
Ji Bo Wang ◽  
Chou Jung Hsu
Keyword(s):  
Objective Function ◽  
Polynomial Time ◽  
Single Machine ◽  
Processing Time ◽  
Optimal Algorithm ◽  
Machine Scheduling ◽  
Single Machine Scheduling ◽  
Scheduling Problem ◽  
Processing Times ◽  
Rejection Penalty

This paper studies a single machine scheduling problem with rejection. Each job has a variable processing time and a rejection penalty. The objective function is to minimize the sum of the makespan of the accepted jobs and the total rejection penalty of the rejected jobs. We show that the problem can be solved in polynomial time.

scholarly journals ILS Heuristics for the Single-Machine Scheduling Problem with Sequence-Dependent Family Setup Times to Minimize Total Tardiness

2016 ◽  
Vol 2016 ◽  
pp. 1-15 ◽  
Author(s):  
Vinícius Vilar Jacob ◽  
José Elias C. Arroyo
Keyword(s):  
Single Machine ◽  
Machine Scheduling ◽  
Single Machine Scheduling ◽  
Setup Times ◽  
Total Tardiness ◽  
Superior Performance ◽  
Scheduling Problem ◽  
Sequence Dependent ◽  
Perturbation Size ◽  
Dynamic Perturbation

This paper addresses a single-machine scheduling problem with sequence-dependent family setup times. In this problem the jobs are classified into families according to their similarity characteristics. Setup times are required on each occasion when the machine switches from processing jobs in one family to jobs in another family. The performance measure to be minimized is the total tardiness with respect to the given due dates of the jobs. The problem is classified asNP-hard in the ordinary sense. Since the computational complexity associated with the mathematical formulation of the problem makes it difficult for optimization solvers to deal with large-sized instances in reasonable solution time, efficient heuristic algorithms are needed to obtain near-optimal solutions. In this work we propose three heuristics based on the Iterated Local Search (ILS) metaheuristic. The first heuristic is a basic ILS, the second uses a dynamic perturbation size, and the third uses a Path Relinking (PR) technique as an intensification strategy. We carry out comprehensive computational and statistical experiments in order to analyze the performance of the proposed heuristics. The computational experiments show that the ILS heuristics outperform a genetic algorithm proposed in the literature. The ILS heuristic with dynamic perturbation size and PR intensification has a superior performance compared to other heuristics.

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