The asymptotic performance ratio of an on-line algorithm for uniform parallel machine scheduling with release dates

2005 ◽  
Vol 106 (1) ◽  
pp. 137-157 ◽  
Author(s):  
Mabel C. Chou ◽  
Maurice Queyranne ◽  
David Simchi-Levi
2021 ◽  
Vol 132 ◽  
pp. 105315
Author(s):  
Nadia Brauner ◽  
Mikhail Y. Kovalyov ◽  
Alain Quilliot ◽  
Hélène Toussaint

Mathematics ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 61
Author(s):  
Wencheng Wang ◽  
Xiaofei Liu

In this paper, we consider parallel-machine scheduling with release times and submodular penalties (P|rj,reject|Cmax+π(R)), in which each job can be accepted and processed on one of m identical parallel machines or rejected, but a penalty must paid if a job is rejected. Each job has a release time and a processing time, and the job can not be processed before its release time. The objective of P|rj,reject|Cmax+π(R) is to minimize the makespan of the accepted jobs plus the penalty of the rejected jobs, where the penalty is determined by a submodular function. This problem generalizes a multiprocessor scheduling problem with rejection, the parallel-machine scheduling with submodular penalties, and the single machine scheduling problem with release dates and submodular rejection penalties. In this paper, inspired by the primal-dual method, we present a combinatorial 2-approximation algorithm to P|rj,reject|Cmax+π(R). This ratio coincides with the best known ratio for the parallel-machine scheduling with submodular penalties and the single machine scheduling problem with release dates and submodular rejection penalties.


2019 ◽  
Vol 11 (24) ◽  
pp. 7137 ◽  
Author(s):  
Jun-Ho Lee ◽  
Hoon Jang

We examine a uniform parallel machine scheduling problem with dedicated machines, job splitting, and limited setup resources for makespan minimization. In this problem, machines have different processing speeds, and each job can only be processed at several designated machines. A job can be split into multiple sections and those sections can be processed on multiple machines simultaneously. Sequence-independent setup times are assumed, and setup operations between jobs require setup operators that are limited. For the problem, we first develop a mathematical optimization model and for large-sized problems a constructive heuristic algorithm is proposed. Finally, we show that the algorithm developed is efficient and provides good solutions by experiments with various scenarios.


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