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LAAS-CRNS, France

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21 Papers

Heuristic Methods for the Antenna-Constrained Beam Layout Optimization on Multibeam Broadcasting Mission

Topics: Optimization; Industrial Engineering; Linear Programming; OR in Telecommunications

Authors: Camille Lescuyer ¹ , Christian Artigues ² , Jean-Thomas Camino ¹ and Cédric Pralet ³

Affiliations: ¹ Airbus Defence and Space, 31 Rue des Cosmonautes, 31402, Toulouse, France , ² CNRS, LAAS, 7 Avenue du Colonel Roche, F-31400, Toulouse, France , ³ ONERA/DTIS, University of Toulouse, 2 Avenue Edouard Belin, 31400 Toulouse, France

Digital Object Identifier: 10.5220/0012380200003639

Proceedings of ICORES 2024, ISBN: 978-989-758-681-1

Quick Abstract

In this paper, we tackle a payload design problem for a broadcasting mission where a telecommunication satellite must provide television services to distinct regions defined as polygons. To cover these polygons, several telecommunication beams are emitted by the satellite, with the risk that they mutually degrade their performance while also being hard to accommodate mechanically on the spacecraft. The problem is to determine a set of non-conflicting beams that cover all the regions and optimize a performance metric related to the sizes of the beams used. The first method is a matheuristic exploiting iterative solv of an ILP model. The second method, called the merge-and-split heuristic, is inspired by Iterated Local Search and reuses a fast graph coloring algorithm to analyze conflicts among selected beams. These two methods are evaluated on realistic instances, the largest one involving more than one hundred regions to cover.

Scheduling Onboard Tasks of the NIMPH Nanosatellite

Topics: Optimization; Scheduling

Authors: Julien Rouzot ^{1

;

2} , Joséphine Gobert ¹ , Christian Artigues ¹ , Romain Boyer ¹ , Frédéric Camps ¹ , Philippe Garnier ² , Emmanuel Hebrard ¹ and Pierre Lopez ¹

Affiliations: ¹ LAAS-CNRS, Toulouse, France , ² IRAP, Toulouse, France

Digital Object Identifier: 10.5220/0012378500003639

Proceedings of ICORES 2024, ISBN: 978-989-758-681-1

Quick Abstract

In the context of terrestrial space missions, thanks to the recent development of micro and nanotechnologies, nanosatellites are becoming increasingly popular for their lower cost and ease of deployment. The NIMPH (Nanosatellite to Investigate Microwave Photonics Hardware) mission is an ongoing academic project aimed at developing and launching such a nanosatellite. The onboard resources on these missions are often very limited, and in our study case, a single onboard computer is responsible for orchestrating the science and avionic tasks of the nanosatellite. These tasks are subject to various constraints, such as frequency, minimum/maximum delay between the execution of the same type of task and strict precedences. This makes the scheduling of the onboard tasks a challenging problem, which is critical for the mission success. In this paper, we tackle the problem of scheduling NIMPH onboard tasks using Constraint Programming methods. Our scheduler demonstrates its performance by generating optimal or near-optimal schedules for the NIMPH nanosatellite.

KHAOS Improvements Using BSpline

Authors: Jérôme Truc and Daniel Sidobre

Affiliation: LAAS-CNRS, Université de Toulouse, CNRS, UPS, Toulouse, France

Digital Object Identifier: 10.5220/0011957000003622

Proceedings of ICCAS 2022, ISBN: 978-989-758-657-6

Quick Abstract

The introduction of BSpline to generate the trajectories for a Kinematic Human Aware Optimization-based System for Reactive Planning of a Flying-Coworker, a multi-rotor drone that collaborates with workers to fetch small objects, is presented. This allows to improve the quality of the motions and helps to better respect the constraints relative to the collaboration with a human.

Multi-Mode RCPSP with Safety Margin Maximization: Models and Algorithms

Topics: Optimization; Linear Programming

Authors: Christian Artigues ¹ , Emmanuel Hebrard ¹ , Alain Quilliot ² and Helene Toussaint ²

Affiliations: ¹ LAAS Laboratory, CNRS, Toulouse, France , ² LIMOS Laboratory, CNRS, Clermont-Ferrand, France

Digital Object Identifier: 10.5220/0010190101290136

Proceedings of ICORES 2021, ISBN: 978-989-758-485-5

Quick Abstract

We study here a variant of the multimode Resource Constrained Project Scheduling problem (RCPSP), which involves continuous modes, and a notion of Safety Margin maximization. Our interest was motivated by a work package inside the GEOSAFE H2020 project, devoted to the design of evacuation plans in face of natural disasters, and more specifically wildfire.

Multi-product, Multi-supplier Order Assignment and Routing for an e-Commerce Application in the Retail Sector

Topics: Network Optimization; Routing; Logistics; OR in Transportation; New Applications of OR

Authors: Louis Rivière ¹ , Christian Artigues ¹ , Azeddine Cheref ¹ , Nicolas Jozefowiez ² , Marie-José Huguet ¹ , Sandra U. Ngueveu ¹ and Vincent Charvillat ^{3

;

4}

Affiliations: ¹ CNRS, LAAS-CNRS, Université de Toulouse, INSA, INP, France , ² LCOMS EA 7306, Université de Lorraine, Metz 57000, France , ³ U Devatics, Toulouse, France , ⁴ Université de Toulouse, IRIT, INP, France

Digital Object Identifier: 10.5220/0010318304380445

Proceedings of ICORES 2021, ISBN: 978-989-758-485-5

Quick Abstract

With the rise of virtualization, the share of e-commerce in the retail market continues to grow in an omnichannel context. We consider an existing software tool, developed by the Devatics company, for pooling inventories in stores to meet online orders. The problem which arises therefore consists in seeking the optimal allocation of a set of customers to stores. In this paper we consider a variant of the offline problem corresponding to an evolution of the existing software, consisting of assigning a set of predefined orders when the transportation cost depends on a delivery tour to the customer locations. We show that the problem corresponds to a vehicle routing problem with additional but standard attributes. A mixed-integer linear programming formulation is given and several heuristics are proposed : a giant tour-based genetic algorithm, a simple cluster-first, route second heuristic and an assignment-based genetic algorithm. Preliminary computational results on a set of realistic problem instances suggest that the assignment-based genetic algorithm better scales as the problem size increases.

A Heuristic Method for the Multi-skill Project Scheduling Problem with Partial Preemption

Topics: Project Management; Optimization; Scheduling

Authors: Oliver Polo-Mejía ¹ , Christian Artigues ² and Pierre Lopez ²

Affiliations: ¹ CEA, DEN, DEC, SETC, St. Paul lez Durance, France, LAAS-CNRS, Université de Toulouse, CNRS, Toulouse and France , ² LAAS-CNRS, Université de Toulouse, CNRS, Toulouse and France

Digital Object Identifier: 10.5220/0007390001110120

Proceedings of ICORES 2019, ISBN: 978-989-758-352-0

Quick Abstract

In this article we consider a new scheduling problem known as the Multi-Skill Project Scheduling Problem with Partial Preemption. The main characteristic of this problem is the way we handle the resources release during the preemption periods: only a subset of resources are released. Since this problem is NP-hard, we propose a greedy algorithm based on priority rules, modeling the subproblem of technicians allocation as a Minimum-Cost Maximum-Flow problem. In order to improve the performance of the greedy algorithm, we propose a randomized tree-based local search algorithm. Computational tests are carried out and analyzed.

Related Ontology Subjects/Areas/Topics (14)

Applications	Knowledge-Based Systems	Project Management
Artificial Intelligence	Methodologies and Technologies	Scheduling
Enterprise Information Systems	Operational Research	Software Engineering
Information Systems Analysis and Specification	Optimization	Symbolic Systems
Knowledge Discovery and Information Retrieval	Pattern Recognition

Feature Model based on Design Pattern for the Service Provider in the Service Oriented Architecture

Topics: Software Engineering; Modeling of Distributed Systems; Tools, Techniques and Methodologies for System Development; Modeling Formalisms, Languages, and Notations (e.g. UML, ER variants); EA and Service Oriented Architecture (SOA)

Authors: Akram Kamoun ¹ , Mohamed Hadj Kacem ¹ , Ahmed Hadj Kacem ¹ and Khalil Drira ²

Affiliations: ¹ National Engineering School of Sfax, Tunisia , ² Université de Toulouse, France

Digital Object Identifier: 10.5220/0006332301110120

Proceedings of ICEIS 2017, ISBN: 978-989-758-248-6

Quick Abstract

In Service Oriented Architecture (SOA), service contracts are widely used for designing and developing the features (e.g., services and capabilities) of Service Providers (SPs). Two of the most widely used traditional service contracts in SOA are: WSDL and WADL. We identify that these service contracts suffer from several problems, like: they only work for SOAP and REST communication technologies and do not rely on modeling SOA Design Patterns (DPs). One benefit of using SOA DPs is that they permit developing proven SPs for different platforms. In order to overcome these problems, we introduce a new DP-based Feature Model (FM), named FMSP, as a service contract that models the variability of SP features including 15 SOA DPs (e.g., Event-driven messaging DP) and their corresponding constraints. This permits to easily identify and develop valid SOA compound DPs. We demonstrate, through a practical case study and a developed tool, that our FMSP allows to automatically generate fully functional, valid, highly customized and DP-based SPs. We also show that our FMSP reduces the required effort and time to develop SPs.

Related Ontology Subjects/Areas/Topics (5)

Enterprise Information Systems		Modeling of Distributed Systems		Tools, Techniques and Methodologies for System Development
Information Systems Analysis and Specification		Software Engineering

Fixed-sequence Single Machine Scheduling and Outbound Delivery Problems

Topics: Optimization; Dynamic Programming; Scheduling; Logistics

Authors: Azeddine Cheref ¹ , Alessandro Agnetis ² , Christian Artigues ³ and Jean-Charles Billaut ⁴

Affiliations: ¹ Université François-Rabelais Tours / CNRS,, CNRS and Univ. de Toulouse, France , ² Universitá degli Studi di Siena, Italy , ³ CNRS and Univ. de Toulouse, France , ⁴ Université François-Rabelais Tours / CNRS and, France

Digital Object Identifier: 10.5220/0005701201450151

Proceedings of ICORES 2016, ISBN: 978-989-758-171-7

Quick Abstract

In this paper, we study an integrated production an outbound delivery scheduling problem with a predefined sequence. The manufacturer has to process a set of jobs on a single machine and deliver them in batches to multiple customers. A single vehicle with limited capacity is used for the delivery. Each job has a processing time and a specific customer location. Starting from the manufacturer location, the vehicle delivers a set of jobs which constitute a batch by taking into account the transportation times. Since the production sequence and delivery sequence are fixed and identical, the problem consists in deciding the composition of batches. We prove that for any regular sum-type objective function of the delivery times, the problem in NP-hard in the ordinary sense and can be solved in pseudopolynomial time. A dynamic programming algorithm is proposed.

Related Ontology Subjects/Areas/Topics (15)

Applications	Knowledge Discovery and Information Retrieval	Optimization
Artificial Intelligence	Knowledge-Based Systems	Pattern Recognition
Dynamic Programming	Logistics	Scheduling
e-Business	Methodologies and Technologies	Software Engineering
Enterprise Information Systems	Operational Research	Symbolic Systems

A Complete Sensor-based System to Navigate Through a Cluttered Environment

Topics: Control and Supervision Systems; Mobile Robots and Autonomous Systems; Guidance, Navigation and Control

Authors: A. Durand-Petiteville ¹ , V. Cadenat ² and N. Ouadah ³

Affiliations: ¹ University of California, United States , ² CNRS, LAAS and Univ. de Toulouse, France , ³ Centre de Développement des Technologies Avancées, Algeria

Digital Object Identifier: 10.5220/0005502201660173

Proceedings of ICINCO 2015, ISBN: 978-989-758-123-6

Quick Abstract

This article deals with the autonomous navigation problem of a mobile robot in a cluttered environment. We propose to have a different perspective than the traditional way of splitting the problem into two categories: the map-based ones and the mapless ones. Here we divide navigation systems into six processes: perception, modeling, localization, planning, action and decision. Then we present how those processes are organized into an architecture to perform a navigation. It is shown that this framework embraces any navigation system proposed in the literature and how it allows to create new combination of processes. We then detail our solution to the problem which mainly consists in coupling sensor-based controllers with a topological map. Moreover we present the used tools that we have developed over the last years as well as the ones from the literature. Finally we present experimentation results of a long-range navigation based on the proposed approach where a robot drives through an environement despite of occlusions and possible collisions due to obstacles.

Related Ontology Subjects/Areas/Topics (4)

Control and Supervision Systems		Mobile Robots and Autonomous Systems		Robotics and Automation
Informatics in Control, Automation and Robotics

Dynamic Obstacle Avoidance using Online Trajectory Time-scaling and Local Replanning

Topics: Mobile Robots and Autonomous Systems; Guidance, Navigation and Control

Authors: Ran Zhao ¹ and Daniel Sidobre ²

Affiliations: ¹ CNRS and Univ. de Toulouse, France , ² Univ. de Toulouse, France

Digital Object Identifier: 10.5220/0005570204140421

Proceedings of ICINCO 2015, ISBN: 978-989-758-123-6

Quick Abstract

In various circumstances, planning at trajectory level is very useful to generate flexible collision-free motions for autonomous robots, especially when the system interacts with humans or human environment. This paper presents a simple and fast obstacle avoidance algorithm that operates at the trajectory level in real-time. The algorithm uses the Velocity Obstacle to obtain the boundary conditions required to avoid a dynamic obstacle, and then adjust the time evolution using the non-linear trajectory time-scaling scheme. A trajectory local replanning method is applied to make a detour when the static obstacles block the advance path of the robot, which leads to failure of implementing time-scaling approach. Cubic polynomial functions are used to describe trajectories, which brings sufficient flexibility in terms of providing higher order smoothness. We applied this algorithm on reaching tasks for a mobile robot. Simulation results demonstrate that the technique can generate collision-free motion in real time.

Related Ontology Subjects/Areas/Topics (3)

Informatics in Control, Automation and Robotics

Mobile Robots and Autonomous Systems

Robotics and Automation

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