07.02.2019

Three papers accepted at ICAPS, AAMAS & TACAS

We are contributing one paper each to the following three top-tier scientific conferences.

The International Conference on Automated Planning and Scheduling (ICAPS) is the premier forum for all topics revolving around planning done by AI systems. The 29th ICAPS takes place in Berkeley, USA, July 11 to 15. The paper of the Algorithm Engineering group is the result of the 2017 Bachelor Project.

The International Conference on Autonomous Agents and Multiagent Systems (AAMAS) is the most influential venue for the theory and practice of agent-based autonomous systems. This year's edition will be held May 13 to 17 in Montreal, Canada. Our contribution was accepted as a short paper.

Finally, the International Conference on Tools and Algorithms for the Construction and Analysis of Systems (TACAS) aims to build rigorous algorithmic tools for the interaction between humans and complex systems. Research in that direction will be presented April 6 to 11 as part of the European Joint Conferences on Theory and Practice of Software in Prague, Czech Republic.

Clean Citation Style 005

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Peters, Jannik; Stephan, Daniel; Amon, Isabel; Gawendowicz, Hans; Lischeid, Julius; Salabarria, Julius; Umland, Jonas; Werner, Felix; Krejca, Martin S.; Rothenberger, Ralf; Kötzing, Timo; Friedrich, Tobias Mixed Integer Programming versus Evolutionary Computation for Optimizing a Hard Real-World Staff Assignment ProblemInternational Conference on Automated Planning and Scheduling (ICAPS) 2019: 541–554

[ Abstract ] [ BibTeX ] [ URL ] [ Download ]

@inproceedings{peters2019mixed,
  abstract = {Assigning staff to engagements according to hard constraints while optimizing several objectives is a task encountered by many companies on a regular basis. Simplified versions of such assignment problems are NP-hard. Despite this, a typical approach to solving them consists of formulating them as mixed integer programming (MIP) problems and using a state-of-the-art solver to get solutions that closely approximate the optimum. In this paper, we consider a complex real-world staff assignment problem encountered by the professional service company KPMG, with the goal of finding an algorithm that solves it faster and with a better solution than a commercial MIP solver. We follow the evolutionary algorithm (EA) metaheuristic and design a search heuristic which iteratively improves a solution using domain-specific mutation operators. Furthermore, we use a flow algorithm to optimally solve a subproblem, which tremendously reduces the search space for the EA. For our real-world instance of the assignment problem, given the same total time budget of \(100\) hours, a parallel EA approach finds a solution that is only \(1.7\)\% away from an upper bound for the (unknown) optimum within under five hours, while the MIP solver Gurobi still has a gap of \(10.5\) \%.},
  author = {Peters, Jannik and Stephan, Daniel and Amon, Isabel and Gawendowicz, Hans and Lischeid, Julius and Salabarria, Julius and Umland, Jonas and Werner, Felix and Krejca, Martin S. and Rothenberger, Ralf and Kötzing, Timo and Friedrich, Tobias},
  booktitle = {International Conference on Automated Planning and Scheduling (ICAPS)},
  keywords = {year2019 martinskrejca felixwerner tobiasfriedrich danielstephan hansgawendowicz jonasumland timokoetzing isabelamon lennartsalabarria jannikpeters juliuslischeid ralfrothenberger icaps},
  pages = {541-554},
  title = {Mixed Integer Programming versus Evolutionary Computation for Optimizing a Hard Real-World Staff Assignment Problem},
  year = 2019
}

Feldotto, Matthias; Lenzner, Pascal; Molitor, Louise; Skopalik, Alexander From Hotelling to Load Balancing: Approximation and the Principle of Minimum DifferentiationAutonomous Agents and Multiagent Systems (AAMAS) 2019: 1949–1951

[ Abstract ] [ BibTeX ] [ URL ] [ Download ]

Bläsius, Thomas; Friedrich, Tobias; Sutton, Andrew M. On the Empirical Time Complexity of Scale-Free 3-SAT at the Phase TransitionTools and Algorithms for the Construction and Analysis of Systems (TACAS) 2019: 117–134

[ Abstract ] [ BibTeX ] [ URL ] [ DOI ] [ Download ]

@inproceedings{blasius2019empirical,
  abstract = {The hardness of formulas at the solubility phase transition of random propositional satisfiability (SAT) has been intensely studied for decades both empirically and theoretically. Solvers based on stochastic local search (SLS) appear to scale very well at the critical threshold, while complete backtracking solvers exhibit exponential scaling. On industrial SAT instances, this phenomenon is inverted: backtracking solvers can tackle large industrial problems, where SLS-based solvers appear to stall. Industrial instances exhibit sharply different structure than uniform random instances. Among many other properties, they are often heterogeneous in the sense that some variables appear in many while others appear in only few clauses. We conjecture that the heterogeneity of SAT formulas alone already contributes to the trade-off in performance between SLS solvers and complete backtracking solvers. We empirically determine how the run time of SLS vs. backtracking solvers depends on the heterogeneity of the input, which is controlled by drawing variables according to a scale-free distribution. Our experiments reveal that the efficiency of complete solvers at the phase transition is strongly related to the heterogeneity of the degree distribution. We report results that suggest the depth of satisfying assignments in complete search trees is influenced by the level of heterogeneity as measured by a power-law exponent. We also find that incomplete SLS solvers, which scale well on uniform instances, are not affected by heterogeneity. The main contribution of this paper utilizes the scale-free random 3-SAT model to isolate heterogeneity as an important factor in the scaling discrepancy between complete and SLS solvers at the uniform phase transition found in previous works.},
  author = {Bläsius, Thomas and Friedrich, Tobias and Sutton, Andrew M.},
  booktitle = {Tools and Algorithms for the Construction and Analysis of Systems (TACAS)},
  keywords = {thomasblaesius year2019 tacas tobiasfriedrich scalefree_sat andrewmsutton},
  pages = {117-134},
  title = {On the Empirical Time Complexity of Scale-Free 3-SAT at the Phase Transition},
  year = 2019
}