E192-02 - Forschungsbereich Databases and Artificial Intelligence
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Journal:
Journal of Artificial Intelligence Research
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ISSN:
1076-9757
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Date (published):
Sep-2019
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Number of Pages:
32
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Publisher:
AI ACCESS FOUNDATION
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Peer reviewed:
Yes
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Keywords:
Artificial Intelligence
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Abstract:
The article presents a solution approach for the Torpedo Scheduling Problem, an operational planning problem found in steel production. The problem consists of the integrated scheduling and routing of torpedo cars, i. e. steel transporting vehicles, from a blast furnace to steel converters. In the continuous metallurgic transformation of iron into steel, the discrete transportation step of molten iron must be planned with considerable care in order to ensure a continuous material flow.
The problem is solved by a Simulated Annealing algorithm, coupled with an approach of reducing the set of feasible material assignments. The latter is based on logical reductions and lower bound calculations on the number of torpedo cars.
Experimental investigations are performed on a larger number of problem instances, which stem from the 2016 implementation challenge of the Association of Constraint Programming (ACP). Our approach was ranked first (joint first place) in the 2016 ACP challenge and found optimal solutions for all used instances in this challenge.
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Project title:
CD Laboratory for Artificial Intelligence and Optimization for Planning and Scheduling (CDG Christian Doppler Forschungsgesellschaft)