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When the future wind direction is uncertain, the tactical decisions of a yacht skipper involve a stochastic routing problem. The objective of this problem is to maximise the probability of reaching the next mark ahead of all the other competitors. This paper describes some numerical experiments that explore the effect of the skipper׳s risk attitude on their policy when match racing another boat. The tidal current at any location is assumed to be negligible, while the wind direction is modelled by a Markov chain. Boat performance in different wind conditions is defined by the output of a velocity prediction program, and we assume a known speed loss for tacking and gybing. We compare strategies that minimise the average time to sail the leg with those that seek to maximise the probability of winning, and show that by adopting different attitudes to risk when leading or trailing the competitor, a skipper can improve their chances of winning.

When the future wind direction is uncertain, the tactical decisions of a yacht skipper involve a stochastic routing problem. The objective of this problem is to maximise the probability of reaching the next mark ahead of all the other competitors. This paper describes a system that models this problem. The tidal current at any location is assumed to be predictable, while the wind forecast is based on current observations. Boat performance in different wind conditions is defined by the output of a velocity prediction program, and we assume a known speed loss for tacking and gybing. The resulting computer program can be used during a yacht race to choose the optimum course, or it can be used for design purposes to simulate yacht races between different design candidates. As an example of application, we compare strategies that minimise the average time to sail the leg, as opposed to those that maximise the probability of winning, and show how optimal routing strategies are different for leading and trailing boats.

Designing yacht rigs using empirical rules of thumb and large margins of safety can result in rigs that are substantially heavier than they need to be. We describe a suite of mathematical programming models for optimizing the dimensions and minimum scantlings of carbon-fibre rigs. By using mixed complementarity models the finite-element analysis of the rig is extended to handle tension-only cable elements in a natural way. This leads to optimization problems that are mathematical programs with equilibrium constraints. We describe models for optimizing pretension in a rig over multiple load cases, and determining rig geometry and material layout to minimize rig self weight moment over a range of sailing cases.

A Simulation Model for Predicting Yacht Match Race Outcomes

We outline the development of a model for predicting the outcome of a yacht match race between two competing designs.
The model is a fixed-time-increment simulation that accounts for the dynamic performance of each yacht. The wind
speed and direction are modelled using hidden Markov chain models. Each yacht is assumed to follow a fixed sailing
strategy determined by a set of simple decision rules. The simulation models both yachts simultaneously and accounts
for interactions between them—for example, when they cross. The model is illustrated by applying it to International
America’s Cup Class designs.

Advances in Optimization in Yacht Performance Analysis

We describe some applications of mathematical optimization techniques to yacht performance analysis. Applications
include sail trim optimization in wind tunnels, match race modelling under uncertainty, and America’s Cup design optimization
under uncertain weather conditions.