A decomposition-based heuristic for stochastic emergency routing problems |
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Affiliation: | 1. College of Business, University of Mary Washington, 1301 College Avenue, Fredericksburg, VA 22401, United States;2. Department of Information Systems, Statistics and Management Science, University of Alabama, Tuscaloosa, AL 35487-0226, United States;3. Department of Information Systems, Statistics and Management Science, University of Alabama, Tuscaloosa, AL 35487-0226, United States;4. Department of Management, College of Business, University of Arkansas at Little Rock, Little Rock, AR 72204, United States;1. Department of Mathematics, College of Natural Sciences, Arba Minch University, Arba Minch, Ethiopia;2. Department of Mathematics, Annamalai University, Annamalainagar - 608002, Tamilnadu, India;1. Information Engineering Department, Universitá Politecnica delle Marche, via Brecce Bianche, 60131 Ancona, Italy;2. Faculty of Mathematics and Computer Science, Eindhoven University of Technology, NL-5600 MB, Eindhoven, The Netherlands;1. Computer Science Department, Instituto Nacional de Astrofísica Óptica y Electrónica (INAOE), Luis Enrique Erro # 1, Puebla 72840, México;2. Faculty of Psychology, Benemérita Universidad Autónoma de Puebla (BUAP), 3 Oriente # 403, Puebla 72000, México;1. Non-Invasive Imaging and Diagnostics Laboratory, Biomedical Engineering Group, Department of Applied Mechanics, Indian Institute of Technology Madras, Chennai-600036, India;2. Department of Electronics and Communication Engineering, CEG Campus, Anna University, Chennai-600025, India |
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Abstract: | This paper proposes a decomposition-based heuristic for a network delivery problem in which relief workers acquire valuable emergency supplies from relief warehouses, and transport them to meet the urgent needs of distressed population centres. The problem context dictates that the relief items reach these population centres before critical deadlines. However, co-ordination challenges and random disruptions introduce uncertainty in both network travel times and the destination deadlines. Hence, relief workers have to negotiate the tension between ensuring a high probability of punctual delivery and maximising the combined value of the relief supplies delivered. For an arbitrary routing scheme which guarantees punctual delivery in an uncertainty-free state of nature, the heuristic yields an upper bound on the probability that, under uncertainty, the routing scheme described will lead to tardy delivery. We demonstrate our solution approach on a small numerical example and glean insights from experiments on a realistically sized problem. Overall, our central model and proposed solution approach are useful to managers who need to evaluate routing options and devise effective operational delivery plans in humanitarian crisis situations. |
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