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An integrated survey of deterministic project scheduling
Institution:1. Mines Saint-Etienne, Univ Clermont Auvergne CNRS, UMR 6158 LIMOS CMP, Department of Manufacturing Sciences and Logistics, F-13541 Gardanne, France;2. Department of Accounting, Auditing and Business Analytics, BI Norwegian Business School, 0484 Oslo, Norway;3. Institute of Industrial Engineering, National Taiwan University, 1, Sec. 4, Roosevelt Rd, Taipei 106, Taiwan;1. Czech Technical University in Prague, Czech Institute of Informatics, Robotics, and Cybernetics, Prague, The Czech Republic;2. Faculty of Economics and Business Administration, Ghent University, Tweekerkenstraat 2, Gent 9000, (Belgium);3. Technology and Operations Management Area, Vlerick Business School, Belgium;4. UCL School of Management, University College London, UK;1. Faculty of Electrical Engineering and Computing, University of Zagreb, Unska 3, Zagreb 10000, Croatia;2. Birkbeck, University of London, Malet St, Bloomsbury, London WC1E 7HX, United Kingdom
Abstract:There have been many survey papers in the area of project scheduling in recent years. These papers have primarily emphasized modeling and algorithmic contributions for specific classes of project scheduling problems, such as net present value (NPV) maximization and makespan minimization, with and without resource constraints. Paralleling these developments has been the research in the area of project scheduling decision support, with its emphasis on data sets, data generation methods, and so on, that are essential to benchmark, evaluate, and compare the new models, algorithms and heuristic techniques. These investigations have extended the frontiers of research and application in all areas of project scheduling and management. In this paper, we survey the vast literature in this area with a perspective that integrates models, data, and optimal and heuristic algorithms, for the major classes of project scheduling problems. We also include recent surveys that have compared commercial project scheduling systems. Finally, we present an overview of web-based decision support systems and discuss the potential of this technology in enabling and facilitating researchers and practitioners in identifying new areas of inquiry and application.
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