Pierre Laroche

Mobile robot localization in dynamic environments using places recognition

We present a new method to localize a mobile robot in dynamic environments. This method is based on place recognition, and a match between places recognized and the sequence of places that the mobile robot is able to see during a run from an initial place to an ending place. Our method gives a coarse idea of the robots position and orientation. Moreover, the robot can determine the actual state of places (i.e. open doors, closed doors).

A new decomposition technique for solving Markov decision processes

In this paper, we present a new tool for automatically solving Markov Decision Processes. Using a predefined partition o fthe MDP, a directed graph is built to decompose the global MDP into small local MDPs which are independently solved. An approximate solution for the global MDP is obtained using local solutions. Our approach has been tested on a mobile robotics application. It allows near-optimal solutions to be obtained in significantly reduced time. We also present preliminary results concerning a parallel implementation.

GraphMDP: A NEW DECOMPOSITION TOOL FOR SOLVING MARKOV DECISION PROCESSES

In this paper, we present a new tool for solving weakly-coupled Markov Decision Processes using decomposition techniques. Using a predefined partition of the MDP, a directed graph is built to decompose the global MDP into small local MDPs which are independently solved. An approximate solution for the global MDP is obtained by combining local solutions. Our approach has been tested on a mobile robotics application. It allows near-optimal solutions to be obtained in significantly reduced time. We also present preliminary results concerning a parallel implantation of our tool.

Bipartite Complete Matching Vertex Interdiction Problem: Application to Robust Nurse Assignment

In this paper, we consider the Robust Nurse Assignment Problem. This consists in finding the maximum number of absences of qualified nurses still permitting an optimal treatment of patients, leading us to the notion of critical jobs. We introduce the Bipartite Complete Matching Vertex Interdiction Problem as the graph formulation of this problem. We show that it can be solved in polynomial time thanks to the integer polytope of an associated sub-problem. Then, we study the polytope associated with the Bipartite Complete Matching Vertex Interdiction Problem. We also extend the well-known Hall theorem to this problem.

Building efficient partial plans using Markov decision processes

Markov decision processes (MDP) have been widely used as a framework for planning under uncertainty. They allow to compute optimal sequences of actions in order to achieve a given goal, accounting for actuator uncertainties. But algorithms classically used to solve MDPs are intractable for problems requiring a large state space. Plans are computed considering the whole state space, without using any knowledge about the initial state of the problem. We propose a new technique to build partial plans for a mobile robot, considering only a restricted MDP which contains a small set of states composing a path between the initial state and the goal state. To ensure good quality of the solution, the path has to be very similar to the one which would have been computed on the whole environment. We present a new method to compute partial plans, showing that representing the environment as a directed graph can be very helpful to find near-optimal paths. Partial plans obtained using this method are very similar to complete plans, and computing times are considerably reduced.

State aggregation for solving Markov decision problems an application to mobile robotics

In this paper we present two state aggregation methods used to build stochastic plans, modelling our environment with Markov decision processes. Classical methods used to compute stochastic plans are highly intractable for problems necessitating a large number of states, such as our robotics application. The use of aggregation techniques allows to reduce the number of states and our methods give nearly optimal plans in a significantly reduced time.

Lower bounds for the makespan minimization in job shops

In this paper we describe a new approach to model and to solve the job shop scheduling problem using a strip packing formulation. The formulation is enhanced by introducing some valid inequalities in order to compute an efficient lower bound.

Bipartite complete matching vertex interdiction problem with incompatibility constraints: Complexity and heuristics

In this paper, we consider the bipartite complete matching vertex interdiction problem, taking into account some incompatibilities existing among the resources to assign. This problem ensures the obtainment of a robust assignment, which is defined by the number of missing resources still allowing a valid assignment. We introduce graph formulations, considering a single time period or several ones. This problem is shown to be NP-hard, even when considering only a single time period. For several time periods, we adapt the graph formulation, allowing us to solve the problem using polynomial heuristics. Two greedy algorithms and a genetic algorithm are proposed and compared on a randomly-generated testbed.

Foreword – Advanced Optimization Approaches and Modern OR-Applications

CODIT‘14 conference or the International Conference on Control, Decision and Information Technologies has been held in Metz from 3 November to 5 November 2014. It has been the occasion to present 141 contributions selected from about 250 submissions (included the special sessions). This event has attracted participants from 34 countries. This special issue is devoted to CODIT’14 but the submission has been also extended to any high-quality paper non-presented at the conference. According to the journal standards, a new review process has been organized and applied to about 40 submitted papers to this special issue, which attempts to present some recent advances on optimisation and operations research and to publish original papers that contribute to the theory, the solution methods, and the applications related to these areas.