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Extending Microsoft Project for Real-World Job-Shop Scheduling

Authors:
Peter Steininger

Keywords: Job-Shop Scheduling, Genetic Algorithms, Job-Shop Benchmarks, Real-World Scheduling Problems

Abstract:
Although production scheduling has attracted the research interest of production economics communities for decades, there still remains a gap between academic research and real-world problems. Genetic Algorithms (GA) constitute a technique that has already been applied already to a variety of combinatorial problems. We will explain the application of a GA approach to bridge this gap for job-shop scheduling problems, for example to minimize makespan of a production program or to increase the due-date reliability of jobs. The presented approach focuses on integrating a scheduling algorithm, based on GA, into a commercial software product, namely Microsoft Project 2003. We extended Microsoft Project in a range of aspects: A new graphical user interface is introduced to support users by a guided wizard describing the problem for which an optimal schedule is sought. The GA was developed to search for the solution with the maximum results for a given set of production logistical objectives. The developed GA algorithm and operators are tested on real-world data from a one-of-a-kind manufacturing department of a major company. It includes different aggregation operators for combining objectives. Furthermore, the efficiency of the algorithm was compared to benchmark tests available in literature.

Pages: 94 to 99

Copyright: Copyright (c) IARIA, 2011

Publication date: November 20, 2011

Published in: conference

ISSN: 2308-4499

ISBN: 978-1-61208-172-4

Location: Lisbon, Portugal

Dates: from November 20, 2011 to November 25, 2011