A variable neighborhood search algorithm for the constrained task allocation problem

A Variable Neighborhood Search algorithm is proposed for solving a task allocation problem whose main characteristics are: (i) each task requires a certain amount of resources and each processor has a finite capacity to be search between task it is assigned; (ii) the cost of solutions includes fixed cost when using processors, assigning cost and communication cost between task assigned to different processors. A computational experiment shows that the algorithm is satisfactory in terms of time and solution qualit

Deriving feasible deployment alternatives for parallel and distributed simulation systems

Cataloged from PDF version of article.Parallel and distributed simulations (PADS) realize the distributed execution of a simulation system over multiple physical resources. To realize the execution of PADS, different simulation infrastructures such as HLA, DIS and TENA have been defined. Recently, the Distributed Simulation Engineering and Execution Process (DSEEP) that supports the mapping of the simulations on the infrastructures has been defined. An important recommended task in DSEEP is the evaluation of the performance of the simulation systems at the design phase. In general, the performance of a simulation is largely influenced by the allocation of member applications to the resources. Usually, the deployment of the applications to the resources can be done in many different ways. DSEEP does not provide a concrete approach for evaluating the deployment alternatives. Moreover, current approaches that can be used for realizing various DSEEP activities do not yet provide adequate support for this purpose. We provide a concrete approach for deriving feasible deployment alternatives based on the simulation system and the available resources. In the approach, first the simulation components and the resources are designed. The design is used to define alternative execution configurations, and based on the design and the execution configuration; a feasible deployment alternative can be algorithmically derived. Tool support is developed for the simulation design, the execution configuration definition and the automatic generation of feasible deployment alternatives. The approach has been applied within a large-scale industrial case study for simulating Electronic Warfare systems. © 2013 ACM

Control and communication systems for automated vehicles cooperation and coordination

Mención Internacional en el título de doctorThe technological advances in the Intelligent Transportation Systems (ITS) are exponentially improving over the last century. The objective is to provide intelligent and innovative services for the different modes of transportation, towards a better, safer, coordinated and smarter transport networks. The Intelligent Transportation Systems (ITS) focus is divided into two main categories; the first is to improve existing components of the transport networks, while the second is to develop intelligent vehicles which facilitate the transportation process. Different research efforts have been exerted to tackle various aspects in the fields of the automated vehicles. Accordingly, this thesis is addressing the problem of multiple automated vehicles cooperation and coordination. At first, 3DCoAutoSim driving simulator was developed in Unity game engine and connected to Robot Operating System (ROS) framework and Simulation of Urban Mobility (SUMO). 3DCoAutoSim is an abbreviation for "3D Simulator for Cooperative Advanced Driver Assistance Systems (ADAS) and Automated Vehicles Simulator". 3DCoAutoSim was tested under different circumstances and conditions, afterward, it was validated through carrying-out several controlled experiments and compare the results against their counter reality experiments. The obtained results showed the efficiency of the simulator to handle different situations, emulating real world vehicles. Next is the development of the iCab platforms, which is an abbreviation for "Intelligent Campus Automobile". The platforms are two electric golf-carts that were modified mechanically, electronically and electrically towards the goal of automated driving. Each iCab was equipped with several on-board embedded computers, perception sensors and auxiliary devices, in order to execute the necessary actions for self-driving. Moreover, the platforms are capable of several Vehicle-to-Everything (V2X) communication schemes, applying three layers of control, utilizing cooperation architecture for platooning, executing localization systems, mapping systems, perception systems, and finally several planning systems. Hundreds of experiments were carried-out for the validation of each system in the iCab platform. Results proved the functionality of the platform to self-drive from one point to another with minimal human intervention.Los avances tecnológicos en Sistemas Inteligentes de Transporte (ITS) han crecido de forma exponencial durante el último siglo. El objetivo de estos avances es el de proveer de sistemas innovadores e inteligentes para ser aplicados a los diferentes medios de transporte, con el fin de conseguir un transporte mas eficiente, seguro, coordinado e inteligente. El foco de los ITS se divide principalmente en dos categorías; la primera es la mejora de los componentes ya existentes en las redes de transporte, mientras que la segunda es la de desarrollar vehículos inteligentes que hagan más fácil y eficiente el transporte. Diferentes esfuerzos de investigación se han llevado a cabo con el fin de solucionar los numerosos aspectos asociados con la conducción autónoma. Esta tesis propone una solución para la cooperación y coordinación de múltiples vehículos. Para ello, en primer lugar se desarrolló un simulador (3DCoAutoSim) de conducción basado en el motor de juegos Unity, conectado al framework Robot Operating System (ROS) y al simulador Simulation of Urban Mobility (SUMO). 3DCoAutoSim ha sido probado en diferentes condiciones y circunstancias, para posteriormente validarlo con resultados a través de varios experimentos reales controlados. Los resultados obtenidos mostraron la eficiencia del simulador para manejar diferentes situaciones, emulando los vehículos en el mundo real. En segundo lugar, se desarrolló la plataforma de investigación Intelligent Campus Automobile (iCab), que consiste en dos carritos eléctricos de golf, que fueron modificados eléctrica, mecánica y electrónicamente para darle capacidades autónomas. Cada iCab se equipó con diferentes computadoras embebidas, sensores de percepción y unidades auxiliares, con la finalidad de transformarlos en vehículos autónomos. Además, se les han dado capacidad de comunicación multimodal (V2X), se les han aplicado tres capas de control, incorporando una arquitectura de cooperación para operación en modo tren, diferentes esquemas de localización, mapeado, percepción y planificación de rutas. Innumerables experimentos han sido realizados para validar cada uno de los diferentes sistemas incorporados. Los resultados prueban la funcionalidad de esta plataforma para realizar conducción autónoma y cooperativa con mínima intervención humana.Programa Oficial de Doctorado en Ingeniería Eléctrica, Electrónica y AutomáticaPresidente: Francisco Javier Otamendi Fernández de la Puebla.- Secretario: Hanno Hildmann.- Vocal: Pietro Cerr

Data Mining for Enhanced Operations Management Decision Making: Applications in Health Care

Data Mining involves the extraction of new knowledge from large data sets. Despite the growing research interest in data mining, however, integrating this extra knowledge into the subsequent decision making processes has received little attention. Within the context of operations management, this integration can occur in two different ways: by providing inputs for an optimization procedure and by analyzing the output of an optimization procedure. In this dissertation, I will begin by introducing a database exploration technique, which is used to improve the drug discovery process of a pharmaceutical company (Samorani et al., 2011). The same procedure is also applied to a mental health clinic\u27s database to predict whether patients will show up at their scheduled appointments. The knowledge obtained with this procedure is then used to improve patient scheduling procedures (Samorani and LaGanga, 2011). I will finally discuss how data mining can be used to learn useful information about the structure of a problem (Samorani and Laguna, 2012)

Modelling and scheduling of heterogeneous computing systems

Ph.DDOCTOR OF PHILOSOPH

Metaheuristic and Multiobjective Approaches for Space Allocation

This thesis presents an investigation on the application of metaheuristic techniques to tackle the space allocation problem in academic institutions. This is a combinatorial optimisation problem which refers to the distribution of the available room space among a set of entities (staff, research students, computer rooms, etc.) in such a way that the space is utilised as efficiently as possible and the additional constraints are satisfied as much as possible. The literature on the application of optimisation techniques to approach the problem mentioned above is scarce. This thesis provides a description and formulation of the problem. It also proposes and compares a range of heuristics for the initialisation of solutions and for neighbourhood exploration. Four well-known metaheuristics (iterative improvement, simulated annealing, tabu search and genetic algorithms) are adapted and tuned for their application to the problem investigated here. The performance of these techniques is assessed and benchmark results are obtained. Also, hybrid approaches are designed that produce sets of high quality and diverse solutions in much shorter time than those required by space administrators who construct solutions manually. The hybrid approaches are also adapted to tackle the space allocation problem from a two-objective perspective. It is also revealed that the use of aggregating functions or relaxed dominance to evaluate solutions in Pareto optimisation, can be more beneficial than the standard dominance relation to enhance the performance of some multiobjective optimisers in some problem domains. A range of single-solution metaheuristics are extended to create hybrid evolutionary approaches based on the scheme of cooperative local search. This scheme promotes the cooperation of a population of local searchers by means of mechanisms to share the information gained during the search. This thesis also reports the best results known so far for a set of test instances of the space allocation problem in academic institutions. This thesis pioneers the application of metaheuristics to solve the space allocation problem. The major contributions are: provides a formulation of the problem together with tests data sets, reports the best known results for these test instances, investigates the multiobjective nature of the problem and proposes a new form of hybridising metaheuristics

Metaheuristic and Multiobjective Approaches for Space Allocation

This thesis presents an investigation on the application of metaheuristic techniques to tackle the space allocation problem in academic institutions. This is a combinatorial optimisation problem which refers to the distribution of the available room space among a set of entities (staff, research students, computer rooms, etc.) in such a way that the space is utilised as efficiently as possible and the additional constraints are satisfied as much as possible. The literature on the application of optimisation techniques to approach the problem mentioned above is scarce. This thesis provides a description and formulation of the problem. It also proposes and compares a range of heuristics for the initialisation of solutions and for neighbourhood exploration. Four well-known metaheuristics (iterative improvement, simulated annealing, tabu search and genetic algorithms) are adapted and tuned for their application to the problem investigated here. The performance of these techniques is assessed and benchmark results are obtained. Also, hybrid approaches are designed that produce sets of high quality and diverse solutions in much shorter time than those required by space administrators who construct solutions manually. The hybrid approaches are also adapted to tackle the space allocation problem from a two-objective perspective. It is also revealed that the use of aggregating functions or relaxed dominance to evaluate solutions in Pareto optimisation, can be more beneficial than the standard dominance relation to enhance the performance of some multiobjective optimisers in some problem domains. A range of single-solution metaheuristics are extended to create hybrid evolutionary approaches based on the scheme of cooperative local search. This scheme promotes the cooperation of a population of local searchers by means of mechanisms to share the information gained during the search. This thesis also reports the best results known so far for a set of test instances of the space allocation problem in academic institutions. This thesis pioneers the application of metaheuristics to solve the space allocation problem. The major contributions are: provides a formulation of the problem together with tests data sets, reports the best known results for these test instances, investigates the multiobjective nature of the problem and proposes a new form of hybridising metaheuristics

Permutational genetic algorithm for the deployment and scheduling of distributed real time systems

[ES] El despliegue y la planificación de tareas y mensajes en sistemas de tiempo real distribuidos son problemas NP-difíciles (NP- hard), por lo que no existen métodos óptimos para solucionarlos en tiempo polinómico. En consecuencia, estos problemas son adecuados para abordarse mediante algoritmos genéricos de búsqueda y optimización. En este artículo se propone un algoritmo genético multiobjetivo basado en una codificación permutacional de las soluciones para abordar el despliegue y la planificación de sistemas de tiempo real distribuidos. Además de desplegar tareas en computadores y de planificar tareas y mensajes, este algoritmo puede minimizar el número de computadores utilizados, la cantidad de recursos computacionales y de comunicaciones empleados y el tiempo de respuesta de peor caso medio de las aplicaciones. Los resultados experimentales muestran que este algoritmo genético permutacional puede desplegar y planificar sistemas de tiempo real distribuidos de forma satisfactoria y en tiempos razonables.[EN] The deployment and scheduling of tasks and messages in distributed real-time systems are NP-hard problems, so there are no optimal methods to solve them in polynomial time. Consequently, these problems are suitable to be approached with generic search and optimisation algorithms. In this paper we propose a multi-objective genetic algorithm based on a permutational solution encoding for the deployment and scheduling of distributed real-time systems. Besides deploying and scheduling tasks and messages, the algorithm can minimize the number of the used computers, the utilization of computing and networking resources and the average worst-case response times of the applications. The experiments show that this genetic algorithm can successfully synthesize complex distributed real-time systems in reasonable times.Azketa, E.; Gutiérrez, JJ.; Di Natale, M.; Almeida, L.; Marcos, M. (2013). Algoritmo genético permutacional para el despliegue y la planificación de sistemas de tiempo real distribuidos. Revista Iberoamericana de Automática e Informática industrial. 10(3):344-355. https://doi.org/10.1016/j.riai.2013.05.006OJS344355103Achterberg, T. (2009). SCIP: solving constraint integer programs. Mathematical Programming Computation, 1(1), 1-41. doi:10.1007/s12532-008-0001-1Boyd, S., Kim, S.-J., Vandenberghe, L., & Hassibi, A. (2007). A tutorial on geometric programming. Optimization and Engineering, 8(1), 67-127. doi:10.1007/s11081-007-9001-7Chen, W.-H., & Lin, C.-S. (2000). A hybrid heuristic to solve a task allocation problem. Computers & Operations Research, 27(3), 287-303. doi:10.1016/s0305-0548(99)00045-3Deb, K., Pratap, A., Agarwal, S., & Meyarivan, T. (2002). A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Transactions on Evolutionary Computation, 6(2), 182-197. doi:10.1109/4235.996017Dick, R. P., & Jha, N. K. (1998). MOGAC: a multiobjective genetic algorithm for hardware-software cosynthesis of distributed embedded systems. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 17(10), 920-935. doi:10.1109/43.728914Garey, M. R., Johnson, D. S., & Sethi, R. (1976). The Complexity of Flowshop and Jobshop Scheduling. Mathematics of Operations Research, 1(2), 117-129. doi:10.1287/moor.1.2.117Glover, F. (1986). Future paths for integer programming and links to artificial intelligence. Computers & Operations Research, 13(5), 533-549. doi:10.1016/0305-0548(86)90048-1Hamann, A., Jersak, M., Richter, K., & Ernst, R. (2006). A framework for modular analysis and exploration of heterogeneous embedded systems. Real-Time Systems, 33(1-3), 101-137. doi:10.1007/s11241-006-6884-xHladik, P.-E., Cambazard, H., Déplanche, A.-M., & Jussien, N. (2008). Solving a real-time allocation problem with constraint programming. Journal of Systems and Software, 81(1), 132-149. doi:10.1016/j.jss.2007.02.032Kirkpatrick, S. (1984). Optimization by simulated annealing: Quantitative studies. Journal of Statistical Physics, 34(5-6), 975-986. doi:10.1007/bf01009452Porto, S. C. S., Kitajima, J. P. F. W., & Ribeiro, C. C. (2000). Performance evaluation of a parallel tabu search task scheduling algorithm. Parallel Computing, 26(1), 73-90. doi:10.1016/s0167-8191(99)00096-4PORTO, S. C. S., & RIBEIRO, C. C. (1995). A TABU SEARCH APPROACH TO TASK SCHEDULING ON HETEROGENEOUS PROCESSORS UNDER PRECEDENCE CONSTRAINTS. International Journal of High Speed Computing, 07(01), 45-71. doi:10.1142/s012905339500004xShang, L., Dick, R. P., & Jha, N. K. (2007). SLOPES: Hardware–Software Cosynthesis of Low-Power Real-Time Distributed Embedded Systems With Dynamically Reconfigurable FPGAs. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 26(3), 508-526. doi:10.1109/tcad.2006.883909Tindell, K. W., Burns, A., & Wellings, A. J. (1992). Allocating hard real-time tasks: An NP-Hard problem made easy. Real-Time Systems, 4(2), 145-165. doi:10.1007/bf00365407Tindell, K., & Clark, J. (1994). Holistic schedulability analysis for distributed hard real-time systems. Microprocessing and Microprogramming, 40(2-3), 117-134. doi:10.1016/0165-6074(94)90080-