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

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