A Two-Stage Resource-Constrained Project Scheduling Model with Proactive and Reactive Strategies Under Uncertainty

The aim of this paper is to develop a two-stage model to obtain a proactive and reactive schedule in resource-constrained project scheduling problems (RCPSP) under uncertainty. In the proactive phase, the highest cumulative instability weight scheduling of resource buffering is selected to optimize the initial schedule, which is arrange the activities in decreasing order by the sum weights of the activity and its successors. For the reactive schedule, the tabu search is employed to ensure the scheduling process execution. Actually, in practice, the uncertain resource availabilities are inevitable in RCPSP. In this situation, the uncertain factors are considered as the fuzzy random variables in this paper, and some properties of fuzzy random variables are discussed. Subsequently, the Particle Swarm Optimization (PSO) algorithm that solve the two-stage model of RCPSP with proactive and reactive strategies under uncertainty is developed. Finally, by testing the example, the effectiveness of the proposed model and approach is validated by the computation results.

[1]  Junzo Watada,et al.  Fuzzy random renewal process with queueing applications , 2009, Comput. Math. Appl..

[2]  Huaiqing Wang,et al.  Multi-agent-based proactive–reactive scheduling for a job shop , 2012 .

[3]  Jiuping Xu,et al.  A fuzzy random resource-constrained scheduling model with multiple projects and its application to a working procedure in a large-scale water conservancy and hydropower construction project , 2012, J. Sched..

[4]  Gintaras V. Reklaitis,et al.  Robust scheduling with processing time uncertainty , 1997 .

[5]  Hidehiko Yamamoto,et al.  New Proactive Time Buffer Heuristics for Robust Project Scheduling , 2012 .

[6]  Erik Demeulemeester,et al.  Reactive scheduling in the multi-mode RCPSP , 2011, Comput. Oper. Res..

[7]  Erik Demeulemeester,et al.  Proactive and reactive strategies for resource-constrained project scheduling with uncertain resource availabilities , 2008, J. Sched..

[8]  Erik Demeulemeester,et al.  Proactive heuristic procedures for robust project scheduling: An experimental analysis , 2008, Eur. J. Oper. Res..

[9]  Roland Heilmann,et al.  Discrete Optimization A branch-and-bound procedure for the multi-mode resource-constrained project scheduling problem with minimum and maximum time lags , 2002 .

[10]  Erik Demeulemeester,et al.  A tabu search procedure for generating robust project baseline schedules under stochastic resource availabilities , 2006 .

[11]  Efstratios N. Pistikopoulos,et al.  Proactive Scheduling under Uncertainty : A Parametric Optimization Approach , 2007 .

[12]  Debjani Chakraborty,et al.  A single-period inventory model with fuzzy random variable demand , 2005, Math. Comput. Model..

[13]  Jiuping Xu,et al.  A novel portfolio selection model in a hybrid uncertain environment , 2009 .

[14]  Erik Demeulemeester,et al.  Proactive policies for the stochastic resource-constrained project scheduling problem , 2011, Eur. J. Oper. Res..

[15]  Junzo Watada,et al.  Fuzzy random renewal reward process and its applications , 2009, Inf. Sci..

[16]  Yury V. Nikulin,et al.  Robustness in combinatorial optimization and scheduling theory: An extended annotated bibliography , 2004 .

[17]  Jonathan F. Bard,et al.  Disruption management for resource-constrained project scheduling , 2005, J. Oper. Res. Soc..