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Innovations and Advanced Techniques in Computer and Information Sciences and Engineering pp 511–518Cite as

Resource Allocation And Its Distributed Implementation

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Abstract

During the execution of a project (investment, innovation etc.), three important parameters must be kept in mind: we have to execute the project as soon as possible, with minimal total cost and not to exceed resource (manpower, materials, engines etc.) availabilities.Why does it important to execute the project as soon as possible with minimal total cost? If more than one company compete for the execution of an investment project, usually the chance of winning the tender will be higher if a company can execute the project with minimal total project time (TPT) and minimal total project cost. This problem could already be handled in the 60s and 70s with network planning (CPM, MPM, PERT etc.), scheduling (Gantt Diagrams, LOB etc.) and other related cost-minimizing (CPM/COST, MPM/COST etc.) techniques. The most difficult problem was to handle the resources. During the execution of a project we must keep in view the resources, because these resources are usually straitened. There are well-defined number of labours, engines and so on.If we would like to execute the project with minimal TPT and minimal total project cost and optimal use of the resources (manpower, materials, engines etc.) the problem becomes easily so hard to solve (already at 5000-10000 activities) that computers available today cannot find the solution within a reasonable time. The real problem is more complicated, because before the execution of the project we can only estimate the duration time, (variable) cost and resource need of activities. In real life it is common that the duration time of project activities cannot be estimated correctly. In this paper a novel algorithm is introduced by which an optimal resource allocation with minimal total cost for any arbitrary project could be determined. Moreover, this algorithm also handles the competences of the human resources.A distributed problem solving environment is also introduced that implements the above mentioned optimal resource allocation algorithm with a parallel branch and bound method. The system is built on the Jini technology [44]. It is a dynamic, service-oriented infrastructure that utilizes spare cycles of networked workstations in an efficient way and solves computation intensive problems more easily due to the parallelization.

Keywords

  • Deterministic Resource Allocation
  • Stochastic Resource Allocation
  • Distributed Systems
  • Handling Competences in Resource Allocation.

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Author information

Authors and Affiliations

  1. Assistant Professor, Department of Management, University of Pannonia, Pannonia

    Zsolt Tiborx Kosztyán

  2. Associate Professor, Department of Marketing and Management, István Széchenyi University of Gyòr, Gyòr

    Andrea Bencsik

  3. PhD Student, Department of Information Systems, University of Pannonia, Pannonia

    Szabolcs Póta

Authors
  1. Zsolt Tiborx Kosztyán
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  2. Andrea Bencsik
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  3. Szabolcs Póta
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Editor information

Editors and Affiliations

  1. University of Bridgeport, CT, USA

    Tarek Sobh

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© 2007 Springer

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Kosztyán, Z.T., Bencsik, A., Póta, S. (2007). Resource Allocation And Its Distributed Implementation. In: Sobh, T. (eds) Innovations and Advanced Techniques in Computer and Information Sciences and Engineering. Springer, Dordrecht. https://doi.org/10.1007/978-1-4020-6268-1_90

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  • DOI: https://doi.org/10.1007/978-1-4020-6268-1_90

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-1-4020-6267-4

  • Online ISBN: 978-1-4020-6268-1

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