We address the problem of scheduling an office delivery service accomplished by mobile robots using a genetic algorithm. We specialize traditional GA crossover operators introducing new criteria such as time, capacity, distance, random choice etc to get the optimal solution. Then we select the best operator, i.e. the operator that finds the optimal solution, using a credit-gain mechanism managed by a roulette wheel method. In this way, the scheduling system becomes more flexible and efficient.
Mobile Robot Scheduling using a Genetic Algorithm enhanced with a Credit Gain Mechanism
BADALONI, SILVANA;FALDA, MARCO
2004
Abstract
We address the problem of scheduling an office delivery service accomplished by mobile robots using a genetic algorithm. We specialize traditional GA crossover operators introducing new criteria such as time, capacity, distance, random choice etc to get the optimal solution. Then we select the best operator, i.e. the operator that finds the optimal solution, using a credit-gain mechanism managed by a roulette wheel method. In this way, the scheduling system becomes more flexible and efficient.
File in questo prodotto:
Non ci sono file associati a questo prodotto.
Pubblicazioni consigliate
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
