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Andries P Engelbrecht - One of the best experts on this subject based on the ideXlab platform.

  • Archive Management for dynamic multi objective optimisation problems using vector evaluated particle swarm optimisation
    Congress on Evolutionary Computation, 2011
    Co-Authors: Marde Helbig, Andries P Engelbrecht
    Abstract:

    Many optimisation problems have more than one objective that are in conflict with one another and that change over time, called dynamic multi-objective problems. To solve these problems an algorithm must be able to track the changing Pareto Optimal Front (POF) over time and find a diverse set of solutions. This requires detecting that a change has occurred in the environment and then responding to the change. Responding to the change also requires to update the Archive of non-dominated solutions that represents the found POF. This paper discusses various ways to manage the Archive solutions when a change occurs in the environment. Furthermore, two new benchmark functions are presented where the POF is discontinuous. The dynamic Vector Evaluation Particle Swarm Optimisation (DVEPSO) algorithm is tested against a variety of benchmark function types and its performance is compared against three state-of-the-art DMOO algorithms.

  • IEEE Congress on Evolutionary Computation - Archive Management for dynamic multi-objective optimisation problems using vector evaluated particle swarm optimisation
    2011 IEEE Congress of Evolutionary Computation (CEC), 2011
    Co-Authors: Marde Helbig, Andries P Engelbrecht
    Abstract:

    Many optimisation problems have more than one objective that are in conflict with one another and that change over time, called dynamic multi-objective problems. To solve these problems an algorithm must be able to track the changing Pareto Optimal Front (POF) over time and find a diverse set of solutions. This requires detecting that a change has occurred in the environment and then responding to the change. Responding to the change also requires to update the Archive of non-dominated solutions that represents the found POF. This paper discusses various ways to manage the Archive solutions when a change occurs in the environment. Furthermore, two new benchmark functions are presented where the POF is discontinuous. The dynamic Vector Evaluation Particle Swarm Optimisation (DVEPSO) algorithm is tested against a variety of benchmark function types and its performance is compared against three state-of-the-art DMOO algorithms.

Marde Helbig - One of the best experts on this subject based on the ideXlab platform.

  • Archive Management for dynamic multi objective optimisation problems using vector evaluated particle swarm optimisation
    Congress on Evolutionary Computation, 2011
    Co-Authors: Marde Helbig, Andries P Engelbrecht
    Abstract:

    Many optimisation problems have more than one objective that are in conflict with one another and that change over time, called dynamic multi-objective problems. To solve these problems an algorithm must be able to track the changing Pareto Optimal Front (POF) over time and find a diverse set of solutions. This requires detecting that a change has occurred in the environment and then responding to the change. Responding to the change also requires to update the Archive of non-dominated solutions that represents the found POF. This paper discusses various ways to manage the Archive solutions when a change occurs in the environment. Furthermore, two new benchmark functions are presented where the POF is discontinuous. The dynamic Vector Evaluation Particle Swarm Optimisation (DVEPSO) algorithm is tested against a variety of benchmark function types and its performance is compared against three state-of-the-art DMOO algorithms.

  • IEEE Congress on Evolutionary Computation - Archive Management for dynamic multi-objective optimisation problems using vector evaluated particle swarm optimisation
    2011 IEEE Congress of Evolutionary Computation (CEC), 2011
    Co-Authors: Marde Helbig, Andries P Engelbrecht
    Abstract:

    Many optimisation problems have more than one objective that are in conflict with one another and that change over time, called dynamic multi-objective problems. To solve these problems an algorithm must be able to track the changing Pareto Optimal Front (POF) over time and find a diverse set of solutions. This requires detecting that a change has occurred in the environment and then responding to the change. Responding to the change also requires to update the Archive of non-dominated solutions that represents the found POF. This paper discusses various ways to manage the Archive solutions when a change occurs in the environment. Furthermore, two new benchmark functions are presented where the POF is discontinuous. The dynamic Vector Evaluation Particle Swarm Optimisation (DVEPSO) algorithm is tested against a variety of benchmark function types and its performance is compared against three state-of-the-art DMOO algorithms.

Eric Yen - One of the best experts on this subject based on the ideXlab platform.

  • Gestalt of a long-term Archive Management system on semantic grid
    2013 International Conference on Computer Applications Technology (ICCAT), 2013
    Co-Authors: Johannes K. Chiang, Eric Yen
    Abstract:

    Long-term preservation (LTP) is an appealing new research area. Its goal is to make the sustainability of Archives lasting for a foreseeable enough time. The efforts are primarily hampered by challenges such as missing of stands, formal methodology and workflow Management during archiving process. Further deficits are failing to keep interoperation among Archives, information loss without any sense of information decay etc. Objective of this research is to develop the LTP of various kinds of documents, independent from the evolution of time and changes in techniques and digital environments. Basic requirements come from integration of storage Management and information Management, securing preservation of data, metadata, indexes, etc. This paper illustrates the evolutionary development of the LTP for Governmental Archive Management and Knowledge Management with respect to aforementioned requirements. Effective search to resources and efficient storage/access on data, consistent user-interface, recovery drawing on co-location back-up, dynamic regulation on authentication and security Management are tasks followed. Then, a pilot Semantic Data Grid and its annotation and service matching mechanisms are described, where the ontologism play a crucial role. Last but not least, experiences learned and the future works with respect to the semantic grid for LTP will be summarized.

  • developing a governmental long term Archive Management system on semantic grid
    한국지능시스템학회 국제학술대회 발표논문집, 2007
    Co-Authors: Johannes K. Chiang, Eric Yen
    Abstract:

    Long-term preservation (LTP) is an appealing new research area. Its goal is to make the sustainability of Archives last for a foreseeable enough time. The efforts are primarily hampered by challenges such as missing of stands, formal methodology and work flow model during archiving, Further deficits are failing to keep interoperation among Archives, information loss without any sense of information decay etc. Objective of this research is to explore thc LTP of various kinds of documents independent from thc evolution of time and changes in techniques and digital environments. Basic requirements come from integration of storage Management and information Management, securing preservation of data, metadata, indexes, etc. This paper presents the evolutionary development of thc LTP process for Governmental Archive Management and Knowledge Management with respect to above requirements. Effective search to resources and efficient storage/access on data, consistent user-interface, recovery drawing on co-location back-up, dynamic regulation on authentication and security Management are tasks followed. Then, a pilot Semantic Data Grid and its annotation and service matching mechanisms are described, where the ontologism play a crucial role. Last but not least, experiences learned and thc future works with respect to the semantic grid for LTP will be summarized.

Johannes K. Chiang - One of the best experts on this subject based on the ideXlab platform.

  • Gestalt of a long-term Archive Management system on semantic grid
    2013 International Conference on Computer Applications Technology (ICCAT), 2013
    Co-Authors: Johannes K. Chiang, Eric Yen
    Abstract:

    Long-term preservation (LTP) is an appealing new research area. Its goal is to make the sustainability of Archives lasting for a foreseeable enough time. The efforts are primarily hampered by challenges such as missing of stands, formal methodology and workflow Management during archiving process. Further deficits are failing to keep interoperation among Archives, information loss without any sense of information decay etc. Objective of this research is to develop the LTP of various kinds of documents, independent from the evolution of time and changes in techniques and digital environments. Basic requirements come from integration of storage Management and information Management, securing preservation of data, metadata, indexes, etc. This paper illustrates the evolutionary development of the LTP for Governmental Archive Management and Knowledge Management with respect to aforementioned requirements. Effective search to resources and efficient storage/access on data, consistent user-interface, recovery drawing on co-location back-up, dynamic regulation on authentication and security Management are tasks followed. Then, a pilot Semantic Data Grid and its annotation and service matching mechanisms are described, where the ontologism play a crucial role. Last but not least, experiences learned and the future works with respect to the semantic grid for LTP will be summarized.

  • developing a governmental long term Archive Management system on semantic grid
    한국지능시스템학회 국제학술대회 발표논문집, 2007
    Co-Authors: Johannes K. Chiang, Eric Yen
    Abstract:

    Long-term preservation (LTP) is an appealing new research area. Its goal is to make the sustainability of Archives last for a foreseeable enough time. The efforts are primarily hampered by challenges such as missing of stands, formal methodology and work flow model during archiving, Further deficits are failing to keep interoperation among Archives, information loss without any sense of information decay etc. Objective of this research is to explore thc LTP of various kinds of documents independent from thc evolution of time and changes in techniques and digital environments. Basic requirements come from integration of storage Management and information Management, securing preservation of data, metadata, indexes, etc. This paper presents the evolutionary development of thc LTP process for Governmental Archive Management and Knowledge Management with respect to above requirements. Effective search to resources and efficient storage/access on data, consistent user-interface, recovery drawing on co-location back-up, dynamic regulation on authentication and security Management are tasks followed. Then, a pilot Semantic Data Grid and its annotation and service matching mechanisms are described, where the ontologism play a crucial role. Last but not least, experiences learned and thc future works with respect to the semantic grid for LTP will be summarized.

Defu Zhang - One of the best experts on this subject based on the ideXlab platform.

  • a petri nets based generic genetic algorithm framework for resource optimization in business processes
    Simulation Modelling Practice and Theory, 2018
    Co-Authors: Vengian Chan, Marlon Dumas, Defu Zhang
    Abstract:

    Abstract Business process simulation (BPS) enables detailed analysis of resource allocation schemes prior to actually deploying and executing the processes. Although BPS has been widely researched in recent years, less attention has been devoted to intelligent optimization of resource allocation in business processes by exploiting simulation outputs. This paper endeavors to combine the power of a genetic algorithm (GA) in finding optimum resource allocation scheme and the benefits of the process simulation. Although GA has been successfully used for finding optimal resource allocation schemes in manufacturing processes, in this previous work the design of these algorithms is ad hoc, meaning that the chromosomes, crossover and selection operators, and fitness functions need to be manually tailored for each problem. In this research, we pioneer to design and implement a Petri Nets based Generic Genetic Algorithm (GGA) framework that can be used to optimize any given business processes which are modeled in Color Petri Nets (CPN). Specifically, the proposed GGA framework is capable of producing an optimized resource allocation scheme for any CPN process model, its task execution times, and the constraints on available resources. The effectiveness of the proposed framework was evaluated on Archive Management workflow at Macau Historical Archives and an insurance claim workflow from an Australian insurance company. In both case studies, the framework identified significantly improved resource allocation scheme relative to the one that existed when the data for the case studies were collected.