An Application of EDA and GA for Permutation Based Spare Part Allocation Problem

摘要

Enterprise Resource management is crucial to the success of any service organizations. Having right resource at the right time at the right place can make a big difference to the quality of their service offering. This paper focuses on spare parts management in a telecom industry as part of the enterprise resource management problem. The traditional way of moving the spare parts within the network is done manually by expert planners. However, this is not efficient as they may not have a global view of supply and demand, considering a large number of spares and potential locations that have to be taken into account when making distribution decisions. We investigate two evolutionary algorithms to solve this problem. The objective is twofold: 1) to identify and implement a permutation based Estimation of Distribution Algorithm for this problem, 2) to perform detail experimental analysis and compare the performance EDA to that of GA, with the goal of enhancing existing spare management software.