In reality, the amount by which an insurer can lower premiums is constrained by borrowing restrictions and the risk inherent in building up a large exposure. Consequently, the effect of constraining the pricing problem is analysed with two forms of constraint: a bounded premium and a solvency ...
is hard to model (e.g. a model may usually apply irrigation in a drought, but previous droughts, or a long drought may mean that irrigation water is not available)” and changes in the adaptive choices available “Disruptive technology: One of the areas where the struggle is predicting the...
The problem to be solved is a linearly constrained minimisation of the Gibbs energy in which gradients are calculated analytically. The solver (a commercial one) uses a sequential quadratic programming method and is based upon work by Gill and others at Stanford. (3) Martyn Corden and Steve ...
Understanding this sum is very closely related to the problem of finding pairs of primes that differ by ; for instance, if one could establish a lower bound then this would easily imply the twin prime conjecture. The (first) Hardy-Littlewood conjecture asserts an asymptotic as for any fixed...
The notion that human activity can be characterised in terms of dynamic systems is a well-established alternative to motor schema approaches. Key to a dyna
The general formulation of a MO problem is to “maximize” f(x) subject to x∈X, where x=(x1,…,xj,…,xn) is a candidate solution vector (or simply solution) consisting of n design (or decision) variables, X⊂Rn is the search domain, and f=(f1,…,fi,…,fm) is a vector ob...
Being able to go beyond pure workforce management to manage “quality” is a key differentiator in this evolution and optimisation of customer experience. With thanks toJeremy PayneatEnghouse Interactive Integration of long-term and short-term planning tools ...
The problem to be solved is a linearly constrained minimisation of the Gibbs energy in which gradients are calculated analytically. The solver (a commercial one) uses a sequential quadratic programming method and is based upon work by Gill and others at Stanford. (3) Martyn Corden and Steve ...
The problem to be solved is a linearly constrained minimisation of the Gibbs energy in which gradients are calculated analytically. The solver (a commercial one) uses a sequential quadratic programming method and is based upon work by Gill and others at Stanford. (3) Martyn Corden and Steve ...
Practically, both constraints set a lower bound on the effective number of constituents. The norm-constraint (3), aims at tackling the problem of concentration in low volatility stocks that is specific to GMV allocation (Clarke et al. 2011). 1.3 Equal risk contribution portfolio The Equal Risk...