Solving a Judge Assignment Problem Using Conjunctions of Global Cost Functions

Abstract

The Asia Pacific Information and Communication Technology Alliance (APICTA) Awards has been held for 12 years, rewarding the most innovative solutions in different categories of Information and Communication Technology (ICT). To maintain professionalism, judges are nominated from each economy, and appointed to panels of different categories. Judge assignment is a difficult task, since it has to optimize between expertise, distribution of workloads, fairness and sometimes even political correctness. In this paper, we describe our experience in analyzing and automating the APICTA judge assignment process using Soft Constraint Programming for the 13 th APICTA hosted in Hong Kong on November, 2013. We chose the weighted constraint satisfaction (WCSP) framework since both hard constraints and preferences can be modeled by cost functions. Consistency algorithms can effect strong propagation by redistributing costs among cost functions. We observe that a number of restrictions in the judge assignment problem involves counting. In our first attempt, we utilized the Soft_Among var global cost function for these counting conditions but we could not solve the problem within a day. Soft_GCC val is another possible global cost function to model counting, which is what we used in the second attempt. We can compute the optimum in a few hours, which is far from practical.We apply similar techniques as Régin to show that the combination of Soft_GCC val and Soft_Among var is flow-based. We further prove that the combination results in a flow-based projection-safe cost function, meaning that soft arc consistencies can be enforced efficiently. By using this combination in our final model, we can solve the judge assignment problem within a few minutes. We consider this a success story where theory and practice meet.