The timely production and distribution of rapidly perishable goods such as concrete is a complex combinatorial optimization problem in the context of supply chain management. The problem involves several tightly interrelated scheduling and routing problems that have to be solved considering a trade-off of production and delivery costs. A hybrid meta-heuristic method combining genetic algorithms with constructive heuristics has been previously presented. This paper introduces a novel approach, by replacing the constructive heuristic with another meta-heuristic, the ant colony optimization approach. The simulation examples show that the concrete supply chain improves the performance with the novel GA-ACO algorithm.
Concrete Delivery using a combination of GA and ACO / C. A., Silva; J. M., Faria; P., Abrantes; J. M. C., Sousa; M., Surico; Naso, David. - (2005), pp. 7633-7638. (Intervento presentato al convegno 44th IEEE Conference on Decision Control/European Control Conference tenutosi a Seville, Spain nel December 12-15, 2005) [10.1109/CDC.2005.1583394].
Concrete Delivery using a combination of GA and ACO
NASO, David
2005-01-01
Abstract
The timely production and distribution of rapidly perishable goods such as concrete is a complex combinatorial optimization problem in the context of supply chain management. The problem involves several tightly interrelated scheduling and routing problems that have to be solved considering a trade-off of production and delivery costs. A hybrid meta-heuristic method combining genetic algorithms with constructive heuristics has been previously presented. This paper introduces a novel approach, by replacing the constructive heuristic with another meta-heuristic, the ant colony optimization approach. The simulation examples show that the concrete supply chain improves the performance with the novel GA-ACO algorithm.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.