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FLAIRS
1998
15 years 3 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 3 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 8 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 7 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»
15 years 2 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...