A decision-support tool for humanitarian distribution planners in the face of congestion at security check-points: a real-world case study

Abstract

In times of armed conflicts, various security check-points are placed by authorities to control the flow of merchandise into and within areas of conflicts. The flow of humanitarian trucks that is added to regular flow of commercial trucks together with the complex security procedures create congestion and long waiting times at the security check-points. This causes distribution costs to increase and shortages of relief-aid to the affected civil people to occur. The present study proposes a decision-support tool to assist planners and policymakers in building efficient plans for the distribution of relief-aid, taking into account congestion at security check-points. The proposed tool is built around a multi-item humanitarian distribution planning model which has as objective to minimise distribution and backordering costs subject to capacity constraints that reflect congestion effects using nonlinear clearing functions. Using the 2014 Gaza war as a case study, we illustrate the application of the proposed tool, model the underlying relief-aid humanitarian supply chain, estimate clearing functions at different security check-points, and conduct computational experiments. Our results show that taking congestion into account in distribution planning reduces average lead times, backorders, and distribution costs.

KEYWORDS:

• Humanitarian distribution planning
• relief-aid distribution
• congestion
• clearing functions

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement (DAS)

Data derived from public domain resources:

The following data are publicly available to support the study's findings:

• The Logistics Cluster database, available at www.logcluster.org.

• The Israeli Crossing Point Authority (https://www.mod.gov.il/).

• UNOCHA's data base (www.ochaopt.org/data).

• The Coordination of Israeli Government Activities in the Territories (COGAT) official website (https://www.gov.il/).

Data available within the article or its supplementary materials:

The authors confirm that the data supporting the study's findings are included in the article and its supplementary materials, which can be found at https://doi.org/10.7910/DVN/R9BAKQ.

Additional information

Funding

This work was supported by Special Research Funds Ghent University [grant number BOF18/DOS/057].

Notes on contributors

Mohanad Rezeq

Mohanad Rezeq is a Ph.D. candidate at Ghent University's Faculty of Economics and Business Administration in Belgium. He earned his bachelor's and master's degrees from Al-Quds University, respectively. His areas of interest in teaching and research include operations management, humanitarian logistics, supply chain planning, and business process management.

Tarik Aouam

Tarik Aouam is Professor of Operations Management at the Faculty of Economics and Business Administration, Ghent University (Belgium). He is also affiliated with Africa Business School, University Mohammed VI Polytechnic, Morocco. He received his PhD in Operations Research from Purdue University (USA) and holds a master's degree in Industrial and Manufacturing Systems Engineering from Kansas State University (USA). His research interests are on the optimization of operations and supply chain systems. He relies on his Operations Research background to develop models and algorithms for coordinating production and logistics decisions within firms and across supply chains. His articles have appeared in leading journals, including Operations research, European journal of operational research, IISE transactions, Computers and operations research, International journal of production economics, Omega, International journal of production research and others. Tarik has taught various operations management, management science and operations research courses at several universities in Europe, USA, and MENA region. He has worked for United Airlines and Intel.

Frederik Gailly

Frederik Gailly is an associate professor at Ghent University. He is member of the UGent Business Informatics research group, which is part of the Faculty of Economics and Business Administration and the CVAMO Flanders Make Core Lab. His research focuses on two relevant information systems research domains: ontology-driven conceptual modelling and the development of methods, techniques and tools that can be used to discover, model, and execute knowledge intensive business processes. Dr. Gailly has published in Business & Information Systems Engineering, Decision Support Systems, Expert Systems with Applications, Health Systems, Information Systems Review, Journal of Information Systems (JIS) and Information Systems Journal (ISJ) and has been guest editor for a special issue on Process Modeling for the International Journal of Accounting Information Systems (IJAIS). He has presented his work in some well- known high-quality academic conferences in Business Informatics (e.g. CAISE, Conceptual Modeling, ICEIS, Business Process Management).