A column-and-cut generation algorithm for planning of Canadian armed forces tactical logistics distribution

The military tactical logistics planning problem addresses the issue of distributing heterogeneous commodities (e.g., food, medical supplies, construction material, ammunition, etc.) to forward operating bases in a theatre of operations using a combination of heterogeneous transportation assets such as logistics trucks and tactical helicopters. Minimizing the logistics operating cost while satisfying the operational demands under time and security constraints is of high importance for the Canadian Armed Forces. In this study, a logistics planning model is developed to explore the trade-offs between the effectiveness and efficiency in military tactical logistics distribution. A mathematical optimization algorithm based on Column-and-Cut generation techniques is developed to find the fleet mix and size of transportation assets to meet different Quality-of-Support (QoS) parameters. This paper presents details of a new column generation decomposition approach and a solution algorithm along with an application example to demonstrate the methodology. Extensive computational results are presented in order to measure the degree of efficiency and scalability of the proposed approach, and to analyze the trade-offs between: (1) delivery time and operating cost; (2) security and operating cost. (C) 2013 Elsevier Ltd. All rights reserved.