Many discrete optimization problems can be formulated as either integer linear programming problems or constraint satisfaction problems. Although ILP methods appear to be more powerful, sometimes constraint programming can solve these problems more quickly. This paper describes a problem in which the difference in performance between the two approaches was particularly marked, since a solution could not be found using ILP.The problem arose in the context of organizing a "progressive party" at a yachting rally. Some yachts were to be designated hosts; the crews of the remaining yachts would then visit the hosts for six successive half-hour periods. A guest crew could not revisit the same host, and two guest crews could not meet more than once. Additional constraints were imposed by the capacities of the host yachts and the crew sizes of the guests.Integer linear programming formulations which included all the constraints resulted in very large models, and despite trying several different strategies, all attempts to find a solution failed. Constraint programming was tried instead and solved the problem very quickly, with a little manual assistance. Reasons for the success of constraint programming in this problem are identified and discussed.

Journal name () Condition monitoring of railway vehicles has been highlighted by the railway industry as a key enabling technology for future system development. The primary uses for this could be the improvement of maintenance procedures and/or the identification of high risk vehicle running conditions. Advanced processing of signals means these tasks could be accomplished without the use of cost prohibitive sensors. This paper presents a system for the on-board detection of low adhesion conditions during the normal operation of a railway vehicle. Two different processing methods are introduced. The first method is a modelbased approach that uses a Kalman-Bucy filter to estimate creep forces, with subsequent post processing for interpretation in to adhesion levels. The second non model-based method targets the assessment of relationships between vehicle dynamic responses to observe any behavioural differences as a result of an adhesion level change. Both methods are evaluated in specific case studies using a British Rail (BR) Mark 3 coach, inclusive of a BR BT-10 bogie, and a generic modern passenger vehicle based on a contemporary bogie design. These vehicles were chosen as typical application opportunities within the UK. The results are validated with data generated by the multi-body simulation software VAMPIRE ® for realistic data inputs, representing a key scientific achievement.

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Areas of extremely low adhesion between the wheel and rail can cause critical problems in traction and braking that can manifest in issues such as signals being passed at danger. There is currently a lack of real time information regarding the state and location of low adhesion areas across rail networks.The study presented here examines the scientific challenges of understanding the change in vehicle running dynamics with variations in adhesion using the latest thinking of adhesion at micro-slip. This understanding supports the generation of suitable low-order dynamic models for use with a model-based estimator that infers adhesion levels in the wheel/rail contact using signals from modest-cost sensors that could be fitted to in-service vehicles.This paper presents verification of this technique by using simulated inertial measurement produced from a high fidelity multibody simulation in a series of 'blind' tests.

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