Modeling and Optimization of a Multi-Objective Ridesharing Problem in the Case of Medical Waste
Mustapha Ahlaqqach1, Jamal Benhra2, Salma Mouatassim3, Safia Lamrani4
1Mustapha Ahlaqqach, Ph.D Student, LRI, OSIL Team, ENSEM, CELOG-ESITH, Casablanca, Morocco, North America.
2Jamal Benhra, Research Director, LRI, OSIL Team, ENSEM, Casablanca, Morocco, North America.
3Salma Mouatassim, Ph.D Student, LRI, OSIL Team, ENSEM Casablanca, Morocco, North America.
4Safia Lamrani, Ph.D Student, LRI , OSIL Team, ENSEM Casablanca, Morocco, North America.
Manuscript received on 25 August 2019 | Revised Manuscript received on 11 September 2019 | Manuscript Published on 17 September 2019 | PP: 1911-1918 | Volume-8 Issue-2S8 August 2019 | Retrieval Number: B11980882S819/2019©BEIESP | DOI: 10.35940/ijrte.B1198.0882S819
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Medical wastes is now a major concern of the world community and more particularly that of Moroccans. Indeed, these wastes, classified as hazardous products, are the source of serious infections, contamination of groundwater and air pollution. Through this paper, we encouraged the use of ridesharing to cope with the risks and costs arising from the logistics of these medical wastes. Thus, we have proposed a mathematical model that governs the multi-objective nature of this logistics and the various constraints associated with it. Since the exact approach had difficulties in large instances, we proposed the Genetic Algorithm and Evolution Strategy as metaheuristic to solve the model. The Evolution Strategy showed its efficiency and stability and therefore we have demonstrated through this metaheuristic the possibility of a compromise between the main objectives of our model.
Keywords: Multi-objective Optimization, Ridesharing, Pickup and Delivery, Heterogeneous Fleet, Reverse Logistic, Heuristic Lab.
Scope of the Article: Biomedical Computing