In this paper location problem analysis is considered in the context of the logistics network. The Grouping Genetic algorithm (GGA) method is employed to solve the location problem. The area of application of the models is in the planning of postharvest logistics systems for a grain crop, in this case rice. In this system, facility locations include growers, silos and markets, which all form part of a logistics systems Partitioning production nodes into groups as markets is used with the overall aim to increase grower profits by improvement of the postharvest transportation of their crops. The study considers the location of markets and their optimum number and size by balancing transportation costs and product prices in the logistics system. GGA partitions production points and generates centroids of point groups as market locations. Fundamental procedures in GGA are presented in this paper. Current research seeks to complete the algorithm by determining control parameters for the full model using new field data. (Author/publisher) For the covering entry of this conference, please see ITRD abstract no. E211825.
Samenvatting