Confirmed speakers

• Jack Edmonds [show abstract]
  (York University)

  For thousands of years the beautiful symmetries of a handful of polyhedra with few dimensions and facets have been at the center of refined mathematics. Since the advent of Turing's computers and operations research, beauty has been found in polyhedra regardless of symmetry, with dimensions and facets as numerous as the stars. Linear algebra is being nudged by great systems of linear inequalities as inputs. ‘Polyhedra’ means their solution sets. ‘Existential polytime’, i.e. NP, means reasonable to prove when true.

• Roman Słowiński [show abstract]
  (Poznan University of Technology and Polish Academy of Sciences)

  Preference-driven evolutionary multiobjective combinatorial optimization
  with Choquet integral preference model

  Roman Słowiński
  Poznań University of Technology and Polish Academy of Sciences

  Joint work with Juergen Branke (University of Warwick), Salvatore Corrente (University of Catania),
  Salvatore Greco (University of Catania and University of Portsmouth)
  and Piotr Zielniewicz (Poznań University of Technology)

  We present an interactive evolutionary multiobjective optimization method applicable to both continuous and combinatorial problems. The search is driven by user’s preferences elicited in form of pairwise comparisons of some non-dominated solutions in successive generations. When choosing the mathematical form of the preference model guiding the search, one faces the usual dilemma: if the preference model is too simplistic (say, linear), it is unlikely to be able to represent adequately the user’s preferences expressed through the pairwise comparisons; on the other hand, if the preference model is too versatile, a lot of preference information is required from the user to narrow down the model’s parameters to a useful degree, i.e., such that the preference relation implied by the model is sufficiently richer than the dominance relation and thus helpful to converge to the most preferred part of the Pareto front. For this reason, we propose a method called NEMO-II-Ch that adapts to the complexity of user’s preferences in the course of successive generations. It starts with a linear additive model, and switches to 2-additive Choquet integral, a preference model permitting to represent interaction between objectives, once the linear additive model is not able to represent the preference information iteratively supplied by the user in terms of pairwise comparisons of feasible solutions. Computational experiments with continuous and combinatorial multiobjective optimization problems prove a good convergence of the proposed method to the most preferred region of the Pareto front for a simulated artificial user. The test problems of the multiobjective combinatorial optimization type are those of knapsack and travelling salesman.

• Erwin Pesch [show abstract]
  (University of Siegen)

  Optimization Problems in Intermodal Transport

  Erwin Pesch
  Universität Siegen

  Attracting a higher share of freight traffic on rail requires freight handling in railway yards that is more efficient, and which includes technical innovations as well as the development of suitable optimization approaches and decision-support systems. In this talk we will review some optimization problems of container processing in railway yards, and analyze basic decision problems and solution approaches for the two most important yard types: conventional railroad and modern railrail transshipment yards. Furthermore, we review some of the relevant literature and identify open research challenges. Additionally we address a scheduling problem that arises in intermodal container transportation, where containers need to be transported between customers (shippers or receivers) and container terminals (rail or maritime) and vice versa. The solution method can be applied to other problems as well.

• Tamás Kis [show abstract]
  (Hungarian Academy of Sciences)

  Machine scheduling with non-renewable resources

  Tamás Kis
  Hungarian Academy of Sciences

  In the talk we overview recent developments in machine scheduling with additional non-renewable resources, like raw materials, money, etc. We will consider problems with resource consuming as well as resource producing jobs, and we will show the connections between these problems, and variants of the knapsack problem. From these connections, we will derive approximation algorithms and inapproximability results for various scheduling problems in the class mentioned above.