Abstract

In the Project Scheduling Problem (PSP), the solution robustness can be understood as the capacity that a baseline has to support the disruptions generated by unplanned events (risks). A robust baseline of the project can be obtained from redundancy based methods, which are considered proactive methods to solve the stochastic project scheduling problem. In this research, three redundancy based methods are evaluated and their performance is compared in terms of robustness. These methods add extra time to the original activities duration in order to face the eventualities that may appear during the project execution. In this article a new indicator to analyze the solution robustness to the Project Scheduling Problem with random duration of activities is proposed. This indicator called Relative Average Deviation (RAD) is defined as the margin of deviation of the activities’ start times in relation to their durations. The RAD is based in a traditional concept that seeks to minimize the value of the differences between the planned start times and the real executed start times. The planned start times were obtained from the project baseline generated by each redundancy based method and the real executed start times were obtained from a simulation process based on Monte Carlo technique. The new indicator was used to evaluate the robustness of three baselines generated by different methods but applied to the same case study. Finally, the results suggest that the Relative Average Deviation (RAD) facilitates the interpretation of the robustness concept because it focuses on analyzing the deviation margin associated with an activity.

Highlights

  • The Stochastic Project Scheduling Problem (SPSP) is a type of mathematical optimization problem that incorporates stochastic parameters within the decision process

  • This procedure was applied to three different models: the expected cost model, which minimizes the expected cost taking into account the time constraints of the project, the α-cost model where the cost is minimized and the contraints are met with at least some given confidence level and the probability maximization model, where the probability that the total cost

  • A new measure to evaluate the robustness is presented. This measure is based in a traditional concept that seeks to minimize the value of the differences between the planned start times in the project baseline and the real executed start times

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Summary

INTRODUCTION

The Stochastic Project Scheduling Problem (SPSP) is a type of mathematical optimization problem that incorporates stochastic parameters within the decision process. In the proactive scheduling case, a robust solution should be provided by the mathematical model, in other words, the baseline generated will require few adjustments every time that the disruptions affect the estimated times For this reason, several robustness measures have been designed to evaluate the performance of the proposed procedures to solve the PSP with non-deterministic activities duration. Herroelen and Leus [25] developed a model to solve the PSP with nondeterministic activity durations and obtained a robust solution using a robustness measure based on the previous research of Leon, Wu, and Storer [26] This measure, called the expected weighted deviation, computes the value of differences between the planned start times and the real executed start times.

THE PSP WITH RANDOM DURATION OF ACTIVITIES
ROBUSTNESS MEASURE PROPOSED
Three methods used to solve the PSP with random duration of activities
11. Installation of benches and games
Case study solution Method A
Method A Method B Method C
Findings
CONCLUSION
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