Activity Delay in Stochastic Project Networks

Buss, Arnold H.; Rosenblatt, Meir J.

doi:10.1287/opre.45.1.126

Cited by 57 publications

(55 citation statements)

References 21 publications

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“…Thus, this article extends the work of Buss and Rosenblatt [6], Benati [5], Sobel et al [34] and Creemers et al [10], who focus on duration risk only, and of Schmidt and Grossmann [33], Jain and Grossmann [21] and De Reyck and Leus [12], who look into technical risk only (although Schmidt and Grossmann [33] also explore the possibility of introducing multiple discrete duration scenarios).…”

Section: Introductionmentioning

confidence: 57%

“…Buss and Rosenblatt [6], Sobel et al [34] and Creemers et al [10] investigate an eNPV objective and use the CTMC described by Kulkarni and Adklakha as a starting point for their algorithms. A similar problem is studied by Benati [5], who proposes a heuristic scheduling rule.…”

Section: Policy Classmentioning

confidence: 99%

“…Unfortunately, late-start scheduling is difficult to implement in case of stochastic durations, and Sobel et al [34] implicitly restrict their attention to scheduling policies that start activities only at the end of other activities. Buss and Rosenblatt [6] partially relax this restriction by starting an activity only after a fixed time interval (delay), but they do not decide which sets of activities to start at what time (all eligible activities are started as soon as possible after their delay). Creemers et al [10] study the same problem as Sobel et al [34] and achieve significant computational performance improvements.…”

Section: Policy Classmentioning

confidence: 99%

“…The generalization in which activity starting times are delayed by a fixed offset beyond their earliest starting time poses significant computational challenges (cf. [6]). The models and algorithms in this article can be extended so that activities can also be started when other activities are 'underway,' and in Section 6, we describe our findings for an experiment where we consider the possible start of new activities after each phase in the PH distribution of each ongoing activity (a setting that gives rise to a larger policy class, hence a larger search space).…”

Section: Policy Classmentioning

confidence: 99%

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Project planning with alternative technologies in uncertain environments

Creemers

Reyck

Leus

2015

European Journal of Operational Research

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Abstract:We investigate project scheduling with stochastic activity durations to maximize the expected net present value. Individual activities also carry a risk of failure, which can cause the overall project to fail. In the project planning literature, such technological uncertainty is typically ignored and project plans are developed only for scenarios in which the project succeeds. To mitigate the risk that an activity's failure jeopardizes the entire project, more than one alternative may exist for reaching the project's objectives. We propose a model that incorporates both the risk of activity failure and the possible pursuit of alternative technologies. We find optimal solutions to the scheduling problem by means of stochastic dynamic programming. Our algorithms prescribe which alternatives need to be explored, and how they should be scheduled. We also examine the impact of the variability of the activity durations on the project's value.

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Section: Introductionmentioning

confidence: 57%

Section: Policy Classmentioning

confidence: 99%

Section: Policy Classmentioning

confidence: 99%

Section: Policy Classmentioning

confidence: 99%

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Project planning with alternative technologies in uncertain environments

Creemers

Reyck

Leus

2015

European Journal of Operational Research

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“…This was first discovered by Kulkarni and Adlakha (1986) for stochastic makespan minimization problems. The result was later extended by Buss and Rosenblatt (1997) to analyze stochastic NPV problems where up to two activities can be delayed. To our knowledge, Sobel et al (2009) were the first to propose a generic reformulation of the stochastic NPV maximization problem as a continuous-time Markov decision process.…”

Section: Stochastic Npv Maximization: Exponential Activity Distributionsmentioning

confidence: 99%

Robust Optimization for the Discrete Time-Cost Tradeoff Problem with Cost Uncertainty

Hazır

Haouari

Erel

2014

Handbook on Project Management and Scheduling Vol. 2

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This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. Exempted from this legal reservation are brief excerpts in connection with reviews or scholarly analysis or material supplied specifically for the purpose of being entered and executed on a computer system, for exclusive use by the purchaser of the work. Duplication of this publication or parts thereof is permitted only under the provisions of the Copyright Law of the Publisher's location, in its current version, and permission for use must always be obtained from Springer. Permissions for use may be obtained through RightsLink at the Copyright Clearance Center. Violations are liable to prosecution under the respective Copyright Law. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. While the advice and information in this book are believed to be true and accurate at the date of publication, neither the authors nor the editors nor the publisher can accept any legal responsibility for any errors or omissions that may be made. The publisher makes no warranty, express or implied, with respect to the material contained herein.Printed on acid-free paper Springer is part of Springer Science+Business Media (www.springer.com) PrefaceThis handbook is devoted to scientific approaches to the management and scheduling of projects. Due to their practical relevance, project management and scheduling have been important subjects of inquiry since the early days of Management Science and Operations Research and remain an active and vibrant field of study. The handbook is meant to provide an overview of some of the most active current areas of research. Each chapter has been written by well-recognized scholars, who have made original contributions to their topic. The handbook covers both theoretical concepts and a wide range of applications. For our general readers, we give a brief introduction to elements of project management and scheduling in the first chapter, where we also survey the contents of this book. We believe that the handbook will be a valuable and comprehensive reference to researchers and practitioners in project management and scheduling and hope that it might stimulate further research in this exciting and practically important field.Short-listing and selecting the contributions to this handbook and working with more than one hundred authors have been a challenging and rewarding experience for us. We are grateful to Günter Sch...

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Scheduling recurrent construction

Schmitt¹,

Faaland²

2004

Naval Research Logistics

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A problem we call recurrent construction involves manufacturing large, complex, expensive products such as airplanes, houses, and ships. Customers order configurations of these products well in advance of due dates for delivery. Early delivery may not be permitted. How should the manufacturer determine when to purchase and release materials before fabrication, assembly, and delivery? Major material expenses, significant penalties for deliveries beyond due dates, and long product makespans in recurrent construction motivate choosing a release timetable that maximizes the net present value of cash flows. Our heuristic first projects an initial schedule that dispatches worker teams to tasks for the backlogged products, and then solves a series of maximal closure problems to find material release times that maximize NPV. This method compares favorably with other well-known work release heuristics in solution quality for large problems over a wide range of operating conditions, including order strength, cost structure, utilization level, batch policy, and uncertainty level. Computation times exhibit near linear growth in problem size.

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Activity Delay in Stochastic Project Networks

Cited by 57 publications

References 21 publications

Project planning with alternative technologies in uncertain environments

Project planning with alternative technologies in uncertain environments

Robust Optimization for the Discrete Time-Cost Tradeoff Problem with Cost Uncertainty

Scheduling recurrent construction

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