Minimizing makespan for arbitrary size jobs with release times on P-batch machines with arbitrary capacities
Document Type
Article
Publication Date
2-1-2017
Abstract
We consider the problem of scheduling a set of arbitrary size jobs with dynamic arrival times on a set of parallel batch machines with arbitrary capacities; our goal is to minimize the makespan. We first give a mathematical model of the problem, and provide a lower bound for the objective function value. Based on different rules of batching the jobs and scheduling the batches on the machines, two meta-heuristics based on Ant Colony Optimization (ACO) are proposed to solve the problem. The performance of the proposed algorithms is evaluated and compared with existing heuristics by computational experiments. Our results show that one of the ACO algorithms consistently finds better solutions than all the others in a reasonable amount of time.
Identifier
84987617461 (Scopus)
Publication Title
Future Generation Computer Systems
External Full Text Location
https://doi.org/10.1016/j.future.2016.07.017
ISSN
0167739X
First Page
22
Last Page
34
Volume
67
Grant
ADXXBZ201509
Fund Ref
National Natural Science Foundation of China
Recommended Citation
Jia, Zhaohong; Li, Xiaohao; and Leung, Joseph Y.T., "Minimizing makespan for arbitrary size jobs with release times on P-batch machines with arbitrary capacities" (2017). Faculty Publications. 9777.
https://digitalcommons.njit.edu/fac_pubs/9777
