Title :
A PSO-GA method to solve a partial shipment and scheduling problem
Author_Institution :
Single Digital & Process Lab., Genetic Electr. Global Res. Center, Shanghai, China
Abstract :
The partial shipment in an inbound transportation process is considered in this paper, in which a given collection of components from a list must be delivered from several possible providers (origins) to one plant (destination). The partial shipment and scheduling problem can be reduced to a vehicle routing problem (VRP) with a variable size fleet of trucks. Based on actual logistics data and business process, a new optimization objective is defined in this paper. A genetic algorithm (GA) with a particle swarm optimization (PSO) operator is proposed to solve the optimization problem. Finally, a series of numerical quantifications are analyzed to illustrate the advantages of the proposed algorithm.
Keywords :
genetic algorithms; goods distribution; particle swarm optimisation; scheduling; transportation; genetic algorithm; inbound transportation process; partial shipment problem; particle swarm optimization; scheduling problem; vehicle routing problem; Biological cells; Gallium nitride; Loading; Routing; Genetic Algorithm; Inbound transportation; Partial shipment; Particle Swarm Optimization; Vehicle routing problem;
Conference_Titel :
Computer Application and System Modeling (ICCASM), 2010 International Conference on
Conference_Location :
Taiyuan
Print_ISBN :
978-1-4244-7235-2
Electronic_ISBN :
978-1-4244-7237-6
DOI :
10.1109/ICCASM.2010.5622769