Location modelling : grouping genetic algorithm using a geographic information systems platform.

Author(s)
Pitaksringkarn, L. & Taylor, M.A.P.
Year
Abstract

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.

Request publication

3 + 9 =
Solve this simple math problem and enter the result. E.g. for 1+3, enter 4.

Publication

Library number
C 34160 (In: C 34141 CD-ROM) /72 /71 / ITRD E211844
Source

In: ATRF 04: papers of the 27th Australasian Transport Research Forum, Volume 27, University of South Australia, Transport Systems Centre, 29 September-1 October 2004, 12 p., ref.

Our collection

This publication is one of our other publications, and part of our extensive collection of road safety literature, that also includes the SWOV publications.