Reinforcement learning (RL) can be impractical for many high dimensional problems because of the computational cost of doing stochastic search in large state spaces. We propose a ...
— We present a decentralized, scalable approach to assembling a group of heterogeneous parts into different products using a swarm of robots. While the assembly plans are predete...
Developing dispatching rules for manufacturing systems is a tedious process, which is time- and cost-consuming. Since there is no good general rule for different scenarios and ob...
: This paper describes a new hybrid technique that combines a Greedy Randomized Adaptive Search Procedure (GRASP) and a genetic algorithm with simulation features in order to solve...
Ana C. Olivera, Mariano Frutos, Jessica Andrea Car...
In 1958, Wagner and Whitin published a seminal paper on the deterministic uncapacitated lot-sizing problem, a fundamental model that is embedded in many practical production plann...