The project focuses on optimizing waste collection vehicle routes in Béni Mellal using the Vehicle Routing Problem (VRP) methodology.

By improving route efficiency, the project aims to reduce operational costs, fuel consumption, and greenhouse gas emissions, while enhancing punctuality and minimizing resident disruptions. 

Authors: 

Houssam BAYOUB;

Fatima Ezzahraa BOUNADAR

Supervisor: Mohamed EL ALAOUI

The project aims to optimize the Capacitated Vehicle Routing Problem (VRP) with multiple depots, focusing on minimizing transportation distances while meeting various operational constraints.

The study involves the company Gastromixte, which plans to expand its delivery network from 10 to 50 cities.

The team implemented the Nearest Neighbor algorithm in Python to create efficient routing strategies.

This approach helps improve logistics efficiency by reducing costs and ensuring timely deliveries, contributing to the company’s strategic growth. 

Authors: 

Siham HASNAOUI;

Majda OUSSIDDAN

Supervisor: Mohamed EL ALAOUI

The project focuses on optimizing waste collection vehicle routes in Béni Mellal using the Vehicle Routing Problem (VRP) methodology.

By improving route efficiency, the project aims to reduce operational costs, fuel consumption, and greenhouse gas emissions, while enhancing punctuality and minimizing resident disruptions. 

Authors: 

Roufaida BABZINE;

Aymane BOUMEZZOUGH;

Meriem EL HARKAOUI 

Supervisor: Mohamed EL ALAOUI

This project is dedicated to creating an efficient algorithm to tackle the Vehicle Routing Problem (VRP) for pharmaceutical products.

By leveraging advanced optimization techniques and heuristic methods, the solution aims to generate optimal routes for each vehicle.

It considers various factors such as customer locations, vehicle capacities, delivery time windows, and distances.

The primary goal is to minimize costs while adhering to all operational constraints, thereby improving distribution efficiency and enhancing customer satisfaction. 

Authors:

Hasnae DRIB;

Khaoula NAJAH;

Chaima TAOUFIK

Supervisor: Mohamed EL ALAOUI

The project focuses on optimizing waste collection vehicle routes in Béni Mellal using the Vehicle Routing Problem (VRP) methodology.

By improving route efficiency, the project aims to reduce operational costs, fuel consumption, and greenhouse gas emissions, while enhancing punctuality and minimizing resident disruptions. 

Authors: 

Mohamed Amine BENAMI;

Anas KERROUMI;

Mohamed OUABBI

Supervisor: Mohamed EL ALAOUI

This project offers a digital solution for managing human resources and transportation means for a delivery company in Marrakech, with the aim of minimizing the time, costs, and efforts associated with delivering orders in the city.

The goal is to increase the company’s profits and maximize customer satisfaction by providing the shortest delivery routes and optimizing the choice of the most suitable transportation method. 

Authors:

Mohamed BERKAOUI;

Abdessamad EL OUAFI;

Saddik ERRAMI

Supervisor: Mohamed EL ALAOUI

This project focuses on optimizing the postal distribution network in the province of Béni Mellal for the postal service BARID ALMAGHREB.

Using the Vehicle Routing Problem (VRP) and linear programming techniques, the primary goal is to minimize the distance traveled by delivery vehicles while ensuring efficient mail and parcel distribution.

The project identified the minimum fleet of vehicles required, optimized routes to improve delivery punctuality, and reduced the environmental footprint of the postal service.

The results demonstrate a significant improvement in operational efficiency and customer satisfaction, while also reducing costs and contributing to a more sustainable management of the postal network. 

Authors:

Hajar BHIHI;

Amina BOUBEKRAOUI 

Supervisor: Mohamed EL ALAOUI

This project explores the optimization of medication delivery to hospitals through the Vehicle Routing Problem (VRP), a method used to determine the most efficient routes for a fleet of vehicles. The primary goal is to ensure that deliveries are fast, secure, and reliable while reducing costs and minimizing environmental impact.

By optimizing vehicle routes, the VRP decreases the total distance traveled and reduces delivery times, enhancing the supply chain’s efficiency.

Additionally, it ensures that vehicles are used to their full capacity, minimizing unnecessary trips and ensuring that hospitals receive the medications they need promptly and efficiently, ultimately contributing to the provision of high-quality patient care. 

Authors:

Imane CHTITA;

Iman DOUMI

Supervisor: Mohamed EL ALAOUI

This report explores the digital optimization of delivery processes within reverse logistics, focusing on the Capacitated Vehicle Routing Problem (CVRP) and its dynamic variant (DCVRP).

We developed Python programs using clustering algorithms and route optimization techniques, tested with non-realistic data sets, to demonstrate potential improvements in efficiency and cost reduction.

The study highlights the value of integrating digital strategies in logistics to achieve significant operational gains.

Our findings emphasize the importance of continuous improvement and adaptability in maintaining competitiveness in the logistics sector. 

Authors:

Hind DIRANE;

Hajar ELOUAFI

Supervisor: Mohamed EL ALAOUI

The poster discusses the optimization of vehicle routes for pharmaceutical delivery services in Béni Mellal, aiming to minimize operational costs and environmental impact.

The study involves 10 vehicles delivering to 48 pharmacies, optimizing routes to balance load distribution and minimize travel distances and times.

The results show generated routes with specific distances, loads, and times for each vehicle, ensuring efficient resource use and timely deliveries.

The total distance covered by all routes is 75.28 km, with a total load of 27,005 kg, completed in 112.92 minutes. 

Author: Salma ELANSARI

Supervisor: Mohamed EL ALAOUI