The proactive and reactive resource-constrained project scheduling problem

Abstract

Uncertainty has become an inevitable aspect of project scheduling. We study the resource-constrained project scheduling problem (RCPSP) with stochastic durations. One of the most studied approaches to deal with stochastic durations is that of proactive and reactive scheduling. In this paper, we formulate an integrated proactive and reactive scheduling problem with a combined cost function which includes a baseline schedule cost as well as costs of a series of reactions. We propose four dynamic programming based models (Models 1-4) that solve the problem until optimality over different classes of policies. We compare our models with each other and with a combination of a traditional proactive solution (STC) and a reactive solution (RP SGS). Computational results show that Model 2 outperforms the traditional solution only when reaction costs are greater than zero. Moreover, Model 3 and Model 4 clearly outperform Model 1 and Model 2 in all settings and the traditional solution in most of the settings.

An ANN-Based Approach for Real-Time Scheduling in Cloud Manufacturing

“…where ϕ j can be defined as Equation (27), which motivates the allocation of MR to process T (c) j as early as possible. (27) As shown in Figure 8, the ANN predicts the completion status of MT.…”

“…Due to the uncertain factors, such as task delay, unit failure, and order insertion, the disturbances become difficult to predict, which means that the proactive rescheduling cannot be used in the real-time environments [26]. As a result, more and more researchers have begun to focus on reactive or hybrid rescheduling methods [27]. One group studied the random resource constrained project scheduling problem.…”

Robust Predictive-Reactive Scheduling: An Information-Based Decision Tree Model

“…In the scheduling literature, approaches that mix a proactive phase aiming at issuing a robust baseline schedule and a reactive phase that adapts the baseline scheduling in case of major disturbances have been widely studied under the proactive-reactive scheduling terminology [11]. Recently [3] remarked that in this series of approaches, the proactive and the reactive phases were rather treated separately while they should mutually influence each other. So in [3,4] the authors propose an integrated proactive reactive approach where they aim to find the best policy, which is in their case a robust initial schedule and a set of reactions giving transitions from a schedule to another schedule in response to a disruption, given a certain reaction cost.…”

“…Recently [3] remarked that in this series of approaches, the proactive and the reactive phases were rather treated separately while they should mutually influence each other. So in [3,4] the authors propose an integrated proactive reactive approach where they aim to find the best policy, which is in their case a robust initial schedule and a set of reactions giving transitions from a schedule to another schedule in response to a disruption, given a certain reaction cost. In a pioneering work, [6] proposed the so-called Just In Case approach, in which they compute a multiple contingent schedule, where transitions from a baseline schedule to alternative schedules were anticipated at some events having a high probability of break.…”

“…Then, we detail the algorithm we designed to solve these problems, namely the general algorithm for building the robust decision tree (Sect. 3) and the algorithm for solving the robust partitioning subproblem (Sect. 4).…”