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Project resources scheduling and leveling using Multi-Attribute Decision Models: Models implementation and case study
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DOI：10.1016/j.eswa.2017.01.035.png)
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Abstract
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Project scheduling is one of the most vital processes in Project Management. It is a widely discussed topic in academic and practical circles due to its importance and complexity. Manpower, machines, materials and equipment are used for the execution of project activities, but these mostly have limited availability, which can constrain project scheduling procedures. Project resources might exceed or fall short of the resource demand in a project's time horizon. These considerations present issues to project managers who must try to properly allocate among these demands in order to achieve a near optimal utilization during a project ' s lifetime. Resource leveling is among the greatest challenges faced by project managers as the success of a project largely depends on it. This is because peaks and valleys in the resource usage histogram are responsible for cost overruns due to the necessary recruitment, dismissal and training of the personnel Moreover, issues may arise regarding the efficient management of available resources given that large peaks correspond to fluctuations in resource allocation during a project ' s life cycle or construction period. To address these issues, resource leveling provides procedures and frameworks that ensure the efficient management of resources to obtain smooth resource usage profiles. These procedures attempt to identify activities that should be delayed to resolve resource over-allocations under time and cost constraints. Given the existence of a variety of available rules that could be followed by project managers to prioritize activities, the paper at hand examines the implementation of five Multi-Attribute Decision Making models and how they perform in the scheduling of a solar park construction project. Namely these models are the Weighted Sum Method, Analytic Hierarchy Process, PROMETHEE, TOPSIS, Ordered Weighted Average (OWA) and Hybrid Weighted Average (HWA). Finally, the derived results are discussed in comparison with those obtained by the standard resource leveling procedures of MS-Project. (C) 2017 Elsevier Ltd. All rights reserved.
Keywords:
Project management
Project scheduling
Resource leveling
Multi-Attribute Decision Models
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