Risk-Aware Project Scheduling for Projects with Varied Risk Levels

Abstract

In this paper we continue research into Risk-Aware Project Scheduling Problem (RAPSP), a new class of project scheduling problems defined in [16], that includes risk management issues typical for real-life scenarios. We introduce a new RAPSP solver inspired by GRASP algorithm used for solving traditional stochastic project scheduling problems and compare it with previously defined methods. We also define a new set of benchmark problems, including a class of projects that may fail completely, and verify the efficacy of all our proactive and reactive approaches (both new and existing) for problems of varying complexity and characteristics.

Monte Carlo Tree Search: a review of recent modifications and applications

“…In Waledzik et al (2015), they describe a method called Proactive UCT (ProUCT) that combines running heuristic solvers with the UCT algorithm. The heuristic solvers create baseline schedules, whereas UCT is responsible for testing various alternative branches caused by dynamic events.…”

Bringing Together Project Simulation and Psychometric Tests: A Business Game Proposal

“…Their existence allowed project managers, consultants and the teams themselves with identifying their working style, utilizing their strengths and avoiding their weaknesses in a day-to-day work. Simulation information technology tools have been applied to various aspects of project management like team management [23], project plan construction [28] and building strategies for responses to security threats [15,16]. Also, a general purpose multi-agent frameworks have been developed in order to design systems for modelling human behaviour [27].…”