A holistic metric approach to solving the dynamic location-allocation problem.

Ankrah, Reginald; Lacroix, Benjamin; McCall, John; Hardwick, Andrew; Conway, Anthony

Abstract

In this paper, we introduce a dynamic variant of the Location-Allocation problem: Dynamic Location-Allocation Problem (DULAP). DULAP involves the location of facilities to service a set of customer demands over a defined horizon. To evaluate a solution to DULAP, we propose two holistic metric approaches: Static and Dynamic Approach. In the static approach, a solution is evaluated with the assumption that customer locations and demand remain constant over a defined horizon. In the dynamic approach, the assumption is made that customer demand, and demographic pattern may change over the defined horizon. We introduce a stochastic model to simulate customer population and distribution over time. We use a Genetic Algorithm and Population-Based Incremental Learning algorithm used in previous work to find robust and satisfactory solutions to DULAP. Results show the dynamic approach of evaluating a solution finds good and robust solutions.

Citation

ANKRAH, R., LACROIX, B., MCCALL, J., HARDWICK, A. and CONWAY, A. 2018. A holistic metric approach to solving the dynamic location-allocation problem. In Bramer, M. and Petridis, M. (eds.) Artificial intelligence xxxv: proceedings of the 38th British Computer Society's Specialist Group on Artificial Intelligence (SGAI) International conference on innovative techniques and applications of artificial intelligence (AI-2018), 11-13 December 2018, Cambridge, UK. Lecture notes in artificial intelligence, 11311. Cham: Springer [online], pages 433-439. Available from: https://doi.org/10.1007/978-3-030-04191-5_35

• Presentation Conference Type: Conference Paper (published)
• Conference Name: 38th British Computer Society's Specialist Group on Artificial Intelligence (SGAI) International conference on innovative techniques and applications of artificial intelligence (AI-2018)
• Start Date: Dec 11, 2018
• End Date: Dec 13, 2018
• Acceptance Date: Sep 3, 2018
• Online Publication Date: Nov 16, 2018
• Publication Date: Dec 31, 2018
• Deposit Date: Jun 18, 2019
• Publicly Available Date: Jun 18, 2019
• Publisher: Springer
• Peer Reviewed: Peer Reviewed
• Pages: 433-439
• Series Title: Lecture notes in computer science
• Series Number: 11311
• Series ISSN: 0302-9743
• Book Title: Artificial intelligence XXXV
• ISBN: 9783030041908
• DOI: https://doi.org/10.1007/978-3-030-04191-5_35
• Keywords: Dynamic uncapacitated location-allocation problem; GA; PBIL; Holistic metric; Stochastic model
• Public URL: https://rgu-repository.worktribe.com/output/249289
• Contract Date: Jun 18, 2019