Multi-objective scheduling of dynamic job shop using variable neighborhood search

Authors:
M. A. Adibi;M. Zandieh;M. Amiri
Affiliations:
Faculty of Industrial and Mechanical Engineering, Qazvin Azad University, Qazvin, Iran;Department of Industrial Management, Management and Accounting Faculty, Shahid Beheshti University, G.C., Tehran, Iran;Department of Industrial Management, Management and Accounting Faculty, Allameh Tabatabaei University, Tehran, Iran
Venue:
Expert Systems with Applications: An International Journal
Year:
2010

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Abstract

Dynamic job shop scheduling that considers random job arrivals and machine breakdowns is studied in this paper. Considering an event driven policy rescheduling, is triggered in response to dynamic events by variable neighborhood search (VNS). A trained artificial neural network (ANN) updates parameters of VNS at any rescheduling point. Also, a multi-objective performance measure is applied as objective function that consists of makespan and tardiness. The proposed method is compared with some common dispatching rules that have widely used in the literature for dynamic job shop scheduling problem. Results illustrate the high effectiveness and efficiency of the proposed method in a variety of shop floor conditions.