Publication
Three-level inventory deployment for a luxury watch company facing various perturbations
Abstract
A well-known Swiss watch brand, active in the top-end luxury market, is facing a complex inventory deployment problem where watches of different models (more than 100 different models) must be dispatched first to wholesalers to finally reach the shops where consumers come in. Along the way, different perturbations are expected at three levels (production plan, demand, and dispatching), and accurate reactions must be taken to fit to these uncertainties. Solution methods are proposed to solve realistic instances. Results show the relevance of the methods and the robustness of the solutions.
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Ontological neighbourhood
Related concepts (13)
Numerical methods for ordinary differential equations
Numerical methods for ordinary differential equations are methods used to find numerical approximations to the solutions of ordinary differential equations (ODEs). Their use is also known as "numerical integration", although this term can also refer to the computation of integrals. Many differential equations cannot be solved exactly. For practical purposes, however – such as in engineering – a numeric approximation to the solution is often sufficient. The algorithms studied here can be used to compute such an approximation.
Runge–Kutta methods
In numerical analysis, the Runge–Kutta methods (ˈrʊŋəˈkʊtɑː ) are a family of implicit and explicit iterative methods, which include the Euler method, used in temporal discretization for the approximate solutions of simultaneous nonlinear equations. These methods were developed around 1900 by the German mathematicians Carl Runge and Wilhelm Kutta. The most widely known member of the Runge–Kutta family is generally referred to as "RK4", the "classic Runge–Kutta method" or simply as "the Runge–Kutta method".
Iterative method
In computational mathematics, an iterative method is a mathematical procedure that uses an initial value to generate a sequence of improving approximate solutions for a class of problems, in which the n-th approximation is derived from the previous ones. A specific implementation with termination criteria for a given iterative method like gradient descent, hill climbing, Newton's method, or quasi-Newton methods like BFGS, is an algorithm of the iterative method.
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