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Large-Scale Benchmarks for the Job Shop Scheduling Problem
This report contains the description of two novel job shop scheduling be...
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Google vs IBM: A Constraint Solving Challenge on the Job-Shop Scheduling Problem
The job-shop scheduling is one of the most studied optimization problems...
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A Generally Applicable, Highly Scalable Measurement Computation and Optimization Approach to Sequential Model-Based Diagnosis
Model-Based Diagnosis deals with the identification of the real cause of...
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Anytime Diagnosis for Reconfiguration
Many domains require scalable algorithms that help to determine diagnose...
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The cyclic job-shop scheduling problem: The new subclass of the job-shop problem and applying the Simulated annealing to solve it
In the paper, the new approach to the scheduling problem are described. ...
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Exact and Metaheuristic Approaches for the Production Leveling Problem
In this paper we introduce a new problem in the field of production plan...
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Robust Order Scheduling in the Fashion Industry: A Multi-Objective Optimization Approach
In the fashion industry, order scheduling focuses on the assignment of p...
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The Scheduling Job-Set Optimization Problem: A Model-Based Diagnosis Approach
A common issue for companies is that the volume of product orders may at times exceed the production capacity. We formally introduce two novel problems dealing with the question which orders to discard or postpone in order to meet certain (timeliness) goals, and try to approach them by means of model-based diagnosis. In thorough analyses, we identify many similarities of the introduced problems to diagnosis problems, but also reveal crucial idiosyncracies and outline ways to handle or leverage them. Finally, a proof-of-concept evaluation on industrial-scale problem instances from a well-known scheduling benchmark suite demonstrates that one of the two formalized problems can be well attacked by out-of-the-box model-based diagnosis tools.
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