We study a new multiobjective job scheduling problem on nonidentical machines with
applications in the car industry, inspired by the problem proposed by the car manufacturer …

The two‐level problem studied in this article consists of optimizing the refueling costs of a
fleet of locomotives over a railway network. The goal consists of determining:(1) the number …

Feature selection in classification can be modeled as a combinatorial optimization problem.
One of the main particularities of this problem is the large amount of time that may be …

Fuel and fuel-related expenses constitute a major part of the operating costs of railway
companies. Hence, improvements in fuel management often lead to significant annual …

Les problèmes d'optimisation combinatoire de grandes tailles sont en général difficiles à
résoudre de façon optimale due à des temps de calcul trop élevés. Afin de pallier ce …

Network flow problems appear in an extensive variety of applications in transportation,
supply chain management, logistics, communication networks, and energy systems, to name …

A metaheuristic is a refined solution method able to find a satisfying solution to a difficult
problem in a reasonable amount of time. A local search metaheuristic works on a single …

In this paper, a new type of local search algorithm is proposed, called Learning Tabu Search
and denoted LTS. It is assumed that any solution of the considered problem can be …

Sažetak A metaheuristic is a refined solution method able to find a satisfying solution to a
difficult problem in a reasonable amount of time. A local search metaheuristic works on a …

This thesis aims at proposing relevant optimization techniques, such as metaheuristics, for
various logistics problems faced by international companies. Four different projects are …