Multi-Agent & Multi-Objective Optimization

The team is interested in the cooperative, decentralized and distributed aspects of decisions, related to the presence of several decision centers that interact in a number of applications. The team conducts research in multi-objective mathematical programming. Within multi-agent optimisation problems, the team is also exploring the search for equilibrium solutions within the meaning of game theory that are also non-Pareto dominated. Finally, the team is interested in distributed combinatorial optimization, especially for reasons of security or respect of private data. Interdisciplinary researches on human factors in combinatorial optimization have also been carried out. 

Lower and uper bounds for a biobjective integer program

Multi-objective combinatorial optimization

The single-objective case is here extended to multiple objectives. Considering the Pareto dominance, the team mainly focuses on a posteriori methods which aim at generating the whole set of non-dominated points in the objective space and a solution for each of them. The ROC team aims to design novel multi-objective mathematical programming approaches (branch-and-cut, column generation) and metaheuristics.

Some publications on multi-objective combinatorial optimization

 

Multi-agent project scheduling problem

Multi-agent combinatorial optimization

In several real-life contexts, there is not a single decision maker responsible for solving the whole problem. This becomes especially true as the size and the complexity of the problems solvable through combinatorial optimization techniques is larger and larger. Multi-agent combinatorial optimization aims at considering the distributed aspects of decision in a combinatorial optimization problem. The team focuses especially on the link with game theory.

Some publications on multi-agent combinatorial optimization

 

Work domain analysis and ecological interface design

Human factors in combinatorial optimization

The team also considers how to conciliate human factors with combinatorial optimization through interdisciplinary studies on practical decision-making.This includes  an interdisciplinary study with cognitive ergonomics that was conducted to enhance human-machine cooperation in transportation scheduling

Some publications in human factors in combinatorial optimization