A Modified Balcik Last Mile Distribution Model for Relief Operations Using Open Road Networks. (2018)

• Record Type: Journal Article
• Authors: Putong, Lance L.; De Leon, Marlene M.
• Is Part Of: Procedia engineering. Volume 212(2018)
• Page Start: 133
• Page End: 140
• Publication Date: 2018
• Subjects: computational science -- disaster management -- last mile distribution -- linear programming -- operations research; Engineering -- Congresses; Engineering -- Periodicals; Engineering; Conference proceedings; Periodicals; 620.005
• DOI: 10.1016/j.proeng.2018.01.018
• Languages: English
• ISSNs: 1877-7058

Abstract

Abstract: The last mile in disaster relief distribution chain is the delivery of goods from a central warehouse to the evacuation centers assigned for a given area. Its effectiveness relies on the proper allocation of each kind of relief good amongst the demand areas on a given frequency. Because these operations involve a limited supply of relief goods, vehicles, and time, it is important to optimize these operations to satisfy as much demand as possible. The study aims to create a linear programming model which provides a set of recommendations on how the current disaster relief supply chain may be carried out, specifically on how distribution operations allocate supplies among demand nodes as well as the routes taken in a day. The areas visited per day would depend on the capacity of the vehicle fleet as well as on the routes that can be used. This linear programming model will use Balcik's last mile distribution model, while modifying it for the relief operations in the Philippines. The model minimizes routing costs as well as penalty costs for unsatisfied demands. Map data is used for determining routes and historical data from previous disasters are used to determine the supply and demand for relief goods while providing a benchmark for results. The model produces recommendations for (1) Demand node schedule, (2) Best route for schedule, (3) Relief good allocation, and (4) Operational costs. It also provides the computational backbone for relief distribution decisions in the Philippines, allowing for more optimal operations in the future.