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FLAIRS
1998
15 years 1 months ago
Optimizing Production Manufacturing Using Reinforcement Learning
Manyindustrial processes involve makingparts with an assemblyof machines, where each machinecarries out an operation on a part, and the finished product requires a wholeseries of ...
Sridhar Mahadevan, Georgios Theocharous
IPCO
2004
107views Optimization» more  IPCO 2004»
15 years 1 months ago
A Robust Optimization Approach to Supply Chain Management
Abstract. We propose a general methodology based on robust optimization to address the problem of optimally controlling a supply chain subject to stochastic demand in discrete time...
Dimitris Bertsimas, Aurélie Thiele
HYBRID
2007
Springer
15 years 6 months ago
Robust, Optimal Predictive Control of Jump Markov Linear Systems Using Particles
Hybrid discrete-continuous models, such as Jump Markov Linear Systems, are convenient tools for representing many real-world systems; in the case of fault detection, discrete jumps...
Lars Blackmore, Askar Bektassov, Masahiro Ono, Bri...
IWINAC
2005
Springer
15 years 5 months ago
Interval-Valued Neural Multi-adjoint Logic Programs
The framework of multi-adjoint logic programming has shown to cover a number of approaches to reason under uncertainty, imprecise data or incomplete information. In previous works,...
Jesús Medina, Enrique Mérida Caserme...
COR
2010
155views more  COR 2010»
14 years 12 months ago
A memetic algorithm for the multi-compartment vehicle routing problem with stochastic demands
The Multi-Compartment Vehicle Routing Problem (MC-VRP) consists of designing transportation routes to satisfy the demands of a set of costumers for several products that because o...
Jorge E. Mendoza, Bruno Castanier, Christelle Gu&e...