Reinforcement learning (RL) methods can successfully solve complex optimization
problems. Our article gives a systematic overview of major types of RL methods, their …

Research in metaheuristics for combinatorial optimization problems has lately experienced
a noteworthy shift towards the hybridization of metaheuristics with other techniques for …

Combinatorial optimization has found applications in numerous fields, from aerospace to
transportation planning and economics. The goal is to find an optimal solution among a finite …

Balancing bike sharing systems is an increasingly important problem, because of the rising
popularity of this mean of transportation. Bike sharing systems need to be balanced so that …

This paper aims at providing project office managers or portfolio-level decision-makers with
an integrated methodology to guide the portfolio selection process. The issue is to define a …

Over the last decades, so-called hybrid optimization approaches have become increasingly
popular for addressing hard optimization problems. In fact, when looking at leading …

Meta-heuristics are generic search methods that are used to solve challenging
combinatorial problems. We describe these methods and highlight their common features …

Ant colony optimization Page 1 Ant Colony Optimization, July 12, 2011, GECCO , Dublin,
Ireland c C. Blum Ant Colony Optimization Christian Blum Albcom Research Group Universitat …

Abstract Search-Based Testing (SBT) uses an evolutionary algorithm to generate test cases.
Traditionally, a random selection is used to generate an initial population and also, less …

De nombreuses applications informatiques nécessitent de résoudre des problèmes de
décision qui sont difficiles d'un point de vue mathématique. La programmation par …