Logistics and Vehicle Routing

There are no mandatory minimum requirements. however, a good working domain (skills) with the Microsoft Excel spreadsheet and, in particular, its solver is recommended.

The possession of knowledge in the field of quantitative techniques and general optimization problems will help in a good understanding of the themes.

The classes will be taught in a theoretical-practical regime, preferably in computer rooms.
The interactive expository methodology will be used in the presentation of fundamental concepts and methods, which will be supported by practical experimentation, applied to problem solving.
The problem-based learning component will seek to bring learning in the classroom closer to situations experienced in the professional practice of logistics and transport.
A collaborative learning strategy (i.e., peer interaction) will also be maintained throughout the semester, through the sharing of proposals identified in the work, in particular, in themes of greater complexity and involvement.
In addition to classes, students are motivated to develop complementary learning through a set of challenges launched throughout the semester.

This course introduces some topics within the scope of logistics, involving, namely, the allocation of resources, the dimensioning and planning of production, the integrated management of stocks, the location of means and services, work shifts, and project planning. Topics in the field of transport are also introduced, involving vehicle routes and the supply chain, in addition to topics involving the analysis of trade flow networks.

Techniques for modeling and solving the proposed problems are studied, and their application in the field of Management and Logistics is promoted. The development and application of models will be supported by appropriate software (Microsoft Excel, lp_solve, VRP). Applied work will be encouraged, focusing on the proposed themes.
The main objectives of this course unit are intended for students to have:
O1 – a good understanding of operational research techniques, with a focus on optimization;
O2 – an adequate understanding of the role of operational research, and in particular optimization, in logistics and transport;
O3 – develop the realization of applied work, focusing on the proposed themes.

At the end of the course, students should have developed abilities and skills, namely:
C1 – identification and delimitation of problems in the field of logistics and transport;
C2 – proposals for solving problems in the field of logistics and transport using optimization tools;
C3 – critical analysis and discussion of the generated solutions.

1 – Logistics and Transport Management – A vision of Linear Programming
1.1 – Modeling techniques.
1.2 – Fundamentals of solving linear models.
1.3 – Economic interpretation of solutions and sensitivity analysis.

2 – Integer and Mixed Linear Programming in the optimization of logistics and transport operations
2.1 – Modeling techniques.
2.2 – Fundamentals of exact and approximate resolution of integer and mixed linear models.
2.3 – Analysis and interpretation of solutions.

3 – Software for solving linear and linear mixed integer models.

4 – Study of PL and PLIM application problems in Logistics

4.2 – Warehouse Layout
4.3 – Dimensioning of Logistics Facilities
4.4 – Integrated stock management
4.5 – Allocation of resources
4.4 – Planning of logistical and production operations

5 – Study of PL and PLIM application problems in Transport
5.1 – Transport and logistics flow
5.2 – Dimensioning of Vehicle Fleets
5.3 – Planning operations and work shifts
5.4 – Capacity Management
5.5 – Vehicle routes

6 – Study of problems and applications to the Supply Chain
6.1 – Location of means and services
6.2 – Project planning
6.3 – Planning of logistics operations in the chain
6.4 – Goods flow networks
6.5 – Networks of international flows of goods – Analysis of flows

NAO

Essential Bibliography

–  Teaching materials produced by the teacher.

–  Hillier, F.S., & Lieberman, G.J. (2013). Introdução à pesquisa operacional. McGraw Hill Brasil.

– Mourão, M.C, Santiago Pinto, L., Simões, O., Valente, J., & Vaz Pato, M. (2011). Investigação Operacional: Exercícios e Aplicações, Dashöfer Holding Ltd., Chipre.

Supplementary Bibliography

–  Langley, C. J., Novack, R. A., Gibson, B., & Coyle, J. J. (2020). Supply chain management: a logistics perspective. Cengage Learning.

–  Jacobs, F. R., Chase, R. B., & Lummus, R. R. (2014). Operations and supply chain management (pp. 533-535). New York, NY: McGraw-Hill/Irwin.

–  Rardin, R. (1998). Optimization in Operations Research, Prentice Hall.

–  Wolsey, L. (1998). Integer Programming, Wiley-Interscience.