Cuong dao duc (5 Ergebnisse)

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    • Sprache: Englisch

      Verlag: LAP LAMBERT Academic Publishing, 2010

      3843376999 / 9783843376990

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      Taschenbuch. Zustand: Neu. Project scheduling, a heuristic approach | AN ADAPTIVE PSO AND GA FOR MULTI-MODE RESOURCE-CONSTRAINED PROJECT SCHEDULING PROBLEMS | Dao Duc Cuong | Taschenbuch | 72 S. | Englisch | 2010 | LAP LAMBERT Academic Publishing | EAN 9783843376990 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

    • Sprache: Englisch

      Verlag: LAP LAMBERT Academic Publishing Nov 2010, 2010

      3843376999 / 9783843376990

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      Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -In the recent years, project scheduling and management has been challenging many researchers and has become an intriguing field of study. There are many factors such as personnel, budget, time, materials,etc. that need to be taken into account before running a project. Practical situations have been successfully modeled in mathematical formulations and many problem test cases have been introduced to deal with project scheduling problems. However, having been proved as NP-hard problem, only projects with small numbers of activities can be solved using linear or integer programming approaches while a real project may involve hundreds or even thousands of tasks or activities to be completed. This study proposes an efficient algorithm based on Adaptive Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) to deal with large-scale project scheduling problems, where an activity can be performed in different modes under precedence relations and resource constraints. 72 pp. Englisch.

    • Sprache: Englisch

      Verlag: LAP LAMBERT Academic Publishing, 2010

      3843376999 / 9783843376990

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      Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In the recent years, project scheduling and management has been challenging many researchers and has become an intriguing field of study. There are many factors such as personnel, budget, time, materials,etc. that need to be taken into account before running a project. Practical situations have been successfully modeled in mathematical formulations and many problem test cases have been introduced to deal with project scheduling problems. However, having been proved as NP-hard problem, only projects with small numbers of activities can be solved using linear or integer programming approaches while a real project may involve hundreds or even thousands of tasks or activities to be completed. This study proposes an efficient algorithm based on Adaptive Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) to deal with large-scale project scheduling problems, where an activity can be performed in different modes under precedence relations and resource constraints.

    • Sprache: Englisch

      Verlag: LAP LAMBERT Academic Publishing, 2010

      3843376999 / 9783843376990

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      Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Cuong Dao DucM.Eng in Industrial Engineering from Asian Institute of Technology in 2009, presently Academic Affairs Officer, PetroVietnam University Project in Vietnam.In the recent years, project scheduling and management has be.

    • Sprache: Englisch

      Verlag: LAP LAMBERT Academic Publishing Nov 2010, 2010

      3843376999 / 9783843376990

      • Softcover
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      Anbieter: buchversandmimpf2000, Emtmannsberg, BAYE, Deutschlandbuchversandmimpf2000

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      Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -In the recent years, project scheduling and management has been challenging many researchers and has become an intriguing field of study. There are many factors such as personnel, budget, time, materials,etc. that need to be taken into account before running a project. Practical situations have been successfully modeled in mathematical formulations and many problem test cases have been introduced to deal with project scheduling problems. However, having been proved as NP-hard problem, only projects with small numbers of activities can be solved using linear or integer programming approaches while a real project may involve hundreds or even thousands of tasks or activities to be completed. This study proposes an efficient algorithm based on Adaptive Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) to deal with large-scale project scheduling problems, where an activity can be performed in different modes under precedence relations and resource constraints.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 72 pp. Englisch.