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Erschienen in: Neural Computing and Applications 5/2015

01.07.2015 | Original Article

Designing an efficient bi-criteria iterated greedy heuristic for simultaneous order scheduling and resource allocation: a balance between cost and lateness measures

Erschienen in: Neural Computing and Applications | Ausgabe 5/2015

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Abstract

In this paper, an iterated greedy (IG) heuristic as an intelligent decision-making algorithm is designed for solving a general variant of order scheduling problem with resource allocation. It is assumed that the processing times can be controlled by allocation of a non-renewable common resource, as it is the case in many real-world processes. In order to jointly minimize the number of late orders and the amount of resources consumed, the global criterion as a multiple criteria decision-making method is adapted. Furthermore, a two-layered IG heuristic is devised as solution method. IG heuristic employs a simple but efficient principle and is easy to implement with high capability of evolutionary performance. In suggested IG, a set of solutions is produced by iterating over a greedy construction heuristic by using both destruction and construction functions and then an improving local search is implemented to further enhance the quality of solutions. The simulation experiments show that the proposed IG heuristic is an effective tool in producing high-qualified solutions with respect to the traditional algorithms.

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Metadaten
Titel
Designing an efficient bi-criteria iterated greedy heuristic for simultaneous order scheduling and resource allocation: a balance between cost and lateness measures
Publikationsdatum
01.07.2015
Erschienen in
Neural Computing and Applications / Ausgabe 5/2015
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-014-1778-7

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